Quantum Algorithm for Linear Programming Problems
NASA Astrophysics Data System (ADS)
Joag, Pramod; Mehendale, Dhananjay
The quantum algorithm (PRL 103, 150502, 2009) solves a system of linear equations with exponential speedup over existing classical algorithms. We show that the above algorithm can be readily adopted in the iterative algorithms for solving linear programming (LP) problems. The first iterative algorithm that we suggest for LP problem follows from duality theory. It consists of finding nonnegative solution of the equation forduality condition; forconstraints imposed by the given primal problem and for constraints imposed by its corresponding dual problem. This problem is called the problem of nonnegative least squares, or simply the NNLS problem. We use a well known method for solving the problem of NNLS due to Lawson and Hanson. This algorithm essentially consists of solving in each iterative step a new system of linear equations . The other iterative algorithms that can be used are those based on interior point methods. The same technique can be adopted for solving network flow problems as these problems can be readily formulated as LP problems. The suggested quantum algorithm cansolveLP problems and Network Flow problems of very large size involving millions of variables.
Menu-Driven Solver Of Linear-Programming Problems
NASA Technical Reports Server (NTRS)
Viterna, L. A.; Ferencz, D.
1992-01-01
Program assists inexperienced user in formulating linear-programming problems. A Linear Program Solver (ALPS) computer program is full-featured LP analysis program. Solves plain linear-programming problems as well as more-complicated mixed-integer and pure-integer programs. Also contains efficient technique for solution of purely binary linear-programming problems. Written entirely in IBM's APL2/PC software, Version 1.01. Packed program contains licensed material, property of IBM (copyright 1988, all rights reserved).
An Algorithm for Linearly Constrained Nonlinear Programming Programming Problems.
1980-01-01
ALGORITHM FOR LINEARLY CONSTRAINED NONLINEAR PROGRAMMING PROBLEMS Mokhtar S. Bazaraa and Jamie J. Goode In this paper an algorithm for solving a linearly...distance pro- gramr.ing, as in the works of Bazaraa and Goode 12], and Wolfe [16 can be used for solving this problem. Special methods that take advantage of...34 Pacific Journal of Mathematics, Volume 16, pp. 1-3, 1966. 2. M. S. Bazaraa and J. j. Goode, "An Algorithm for Finding the Shortest Element of a
On Solving Linear Complementarity Problems as Linear Programs.
1976-03-01
obtainedb, •,. b ,.,. the linear program minimize rTv . subject to q + Yv > 0, Xv > 0 19 ,., for any positive vector r Rn Letting x Xv, we see that x is...1.21 1.6 3352 .81 1.7 2353 .65 .8 1490 .50 1.9 664 .37 ti TABLE 4 ,43 i Inputs: n1 7. qT (,-1, -4, 6, -5, 3, -2) starting iterate x y 0 ; original
Symmetry Groups for Linear Programming Relaxations of Orthogonal Array Problems
2015-03-26
Symmetry Groups for Linear Programming Relaxations of Orthogonal Array Problems THESIS MARCH 2015 David M. Arquette, Second Lieutenant, USAF AFIT-ENC...work of the U.S. Government and is not subject to copyright protection in the United States. AFIT-ENC-MS-15-M-003 SYMMETRY GROUPS FOR LINEAR...PUBLIC RELEASE; DISTRIBUTION UNLIMITED. AFIT-ENC-MS-15-M-003 SYMMETRY GROUPS FOR LINEAR PROGRAMMING RELAXATIONS OF ORTHOGONAL ARRAY PROBLEMS David M
Linear Programming and Its Application to Pattern Recognition Problems
NASA Technical Reports Server (NTRS)
Omalley, M. J.
1973-01-01
Linear programming and linear programming like techniques as applied to pattern recognition problems are discussed. Three relatively recent research articles on such applications are summarized. The main results of each paper are described, indicating the theoretical tools needed to obtain them. A synopsis of the author's comments is presented with regard to the applicability or non-applicability of his methods to particular problems, including computational results wherever given.
Solving linear integer programming problems by a novel neural model.
Cavalieri, S
1999-02-01
The paper deals with integer linear programming problems. As is well known, these are extremely complex problems, even when the number of integer variables is quite low. Literature provides examples of various methods to solve such problems, some of which are of a heuristic nature. This paper proposes an alternative strategy based on the Hopfield neural network. The advantage of the strategy essentially lies in the fact that hardware implementation of the neural model allows for the time required to obtain a solution so as not depend on the size of the problem to be solved. The paper presents a particular class of integer linear programming problems, including well-known problems such as the Travelling Salesman Problem and the Set Covering Problem. After a brief description of this class of problems, it is demonstrated that the original Hopfield model is incapable of supplying valid solutions. This is attributed to the presence of constant bias currents in the dynamic of the neural model. A demonstration of this is given and then a novel neural model is presented which continues to be based on the same architecture as the Hopfield model, but introduces modifications thanks to which the integer linear programming problems presented can be solved. Some numerical examples and concluding remarks highlight the solving capacity of the novel neural model.
Efficient numerical methods for entropy-linear programming problems
NASA Astrophysics Data System (ADS)
Gasnikov, A. V.; Gasnikova, E. B.; Nesterov, Yu. E.; Chernov, A. V.
2016-04-01
Entropy-linear programming (ELP) problems arise in various applications. They are usually written as the maximization of entropy (minimization of minus entropy) under affine constraints. In this work, new numerical methods for solving ELP problems are proposed. Sharp estimates for the convergence rates of the proposed methods are established. The approach described applies to a broader class of minimization problems for strongly convex functionals with affine constraints.
Linear decomposition approach for a class of nonconvex programming problems.
Shen, Peiping; Wang, Chunfeng
2017-01-01
This paper presents a linear decomposition approach for a class of nonconvex programming problems by dividing the input space into polynomially many grids. It shows that under certain assumptions the original problem can be transformed and decomposed into a polynomial number of equivalent linear programming subproblems. Based on solving a series of liner programming subproblems corresponding to those grid points we can obtain the near-optimal solution of the original problem. Compared to existing results in the literature, the proposed algorithm does not require the assumptions of quasi-concavity and differentiability of the objective function, and it differs significantly giving an interesting approach to solving the problem with a reduced running time.
Multiobjective fuzzy stochastic linear programming problems with inexact probability distribution
Hamadameen, Abdulqader Othman; Zainuddin, Zaitul Marlizawati
2014-06-19
This study deals with multiobjective fuzzy stochastic linear programming problems with uncertainty probability distribution which are defined as fuzzy assertions by ambiguous experts. The problem formulation has been presented and the two solutions strategies are; the fuzzy transformation via ranking function and the stochastic transformation when α{sup –}. cut technique and linguistic hedges are used in the uncertainty probability distribution. The development of Sen’s method is employed to find a compromise solution, supported by illustrative numerical example.
Multiobjective fuzzy stochastic linear programming problems with inexact probability distribution
NASA Astrophysics Data System (ADS)
Hamadameen, Abdulqader Othman; Zainuddin, Zaitul Marlizawati
2014-06-01
This study deals with multiobjective fuzzy stochastic linear programming problems with uncertainty probability distribution which are defined as fuzzy assertions by ambiguous experts. The problem formulation has been presented and the two solutions strategies are; the fuzzy transformation via ranking function and the stochastic transformation when α-. cut technique and linguistic hedges are used in the uncertainty probability distribution. The development of Sen's method is employed to find a compromise solution, supported by illustrative numerical example.
Hierarchical Multiobjective Linear Programming Problems with Fuzzy Domination Structures
NASA Astrophysics Data System (ADS)
Yano, Hitoshi
2010-10-01
In this paper, we focus on hierarchical multiobjective linear programming problems with fuzzy domination structures where multiple decision makers in a hierarchical organization have their own multiple objective linear functions together with common linear constraints. After introducing decision powers and the solution concept based on the α-level set for the fuzzy convex cone Λ which reflects a fuzzy domination structure, we propose a fuzzy approach to obtain a satisfactory solution which reflects not only the hierarchical relationships between multiple decision makers but also their own preferences for their membership functions. In the proposed method, instead of Pareto optimal concept, a generalized Λ˜α-extreme point concept is introduced. In order to obtain a satisfactory solution from among a generalized Λ˜α-extreme point set, an interactive algorithm based on linear programming is proposed, and an interactive processes are demonstrated by means of an illustrative numerical example.
EZLP: An Interactive Computer Program for Solving Linear Programming Problems. Final Report.
ERIC Educational Resources Information Center
Jarvis, John J.; And Others
Designed for student use in solving linear programming problems, the interactive computer program described (EZLP) permits the student to input the linear programming model in exactly the same manner in which it would be written on paper. This report includes a brief review of the development of EZLP; narrative descriptions of program features,…
An Algorithm for Solving Interval Linear Programming Problems
1974-11-01
34regularized" a lä Chames -Cooper so that infeasibility is determined at optimal solution if that is the case. If I(x*(v)) - 0 then x*(v) is an... Chames and Cooper J3]) may be used to compute the new inverse. Theorem 2 The algorithm described above terminates in a finite number of steps...I J 19- REFERENCES 1) A. Ben-Israel and A. Chames , "An Explicit Solution of A Special Class of Linear Programming Problems", Operations
Extracting Embedded Generalized Networks from Linear Programming Problems.
1984-09-01
E EXTRACTING EMBEDDED GENERALIZED NETWORKS FROM LINEAR PROGRAMMING PROBLEMS by Gerald G. Brown * . ___Richard D. McBride * R. Kevin Wood LcL7...authorized. EA Gerald ’Brown Richar-rD. McBride 46;val Postgrduate School University of Southern California Monterey, California 93943 Los Angeles...REOT UBE . OV S.SF- PERFOING’ CAORG soN UER. 7. AUTNOR(a) S. CONTRACT ON GRANT NUME111() Gerald G. Brown Richard D. McBride S. PERFORMING ORGANIZATION
A recurrent neural network for solving bilevel linear programming problem.
He, Xing; Li, Chuandong; Huang, Tingwen; Li, Chaojie; Huang, Junjian
2014-04-01
In this brief, based on the method of penalty functions, a recurrent neural network (NN) modeled by means of a differential inclusion is proposed for solving the bilevel linear programming problem (BLPP). Compared with the existing NNs for BLPP, the model has the least number of state variables and simple structure. Using nonsmooth analysis, the theory of differential inclusions, and Lyapunov-like method, the equilibrium point sequence of the proposed NNs can approximately converge to an optimal solution of BLPP under certain conditions. Finally, the numerical simulations of a supply chain distribution model have shown excellent performance of the proposed recurrent NNs.
Zhao, Yingfeng; Liu, Sanyang
2016-01-01
We present a practical branch and bound algorithm for globally solving generalized linear multiplicative programming problem with multiplicative constraints. To solve the problem, a relaxation programming problem which is equivalent to a linear programming is proposed by utilizing a new two-phase relaxation technique. In the algorithm, lower and upper bounds are simultaneously obtained by solving some linear relaxation programming problems. Global convergence has been proved and results of some sample examples and a small random experiment show that the proposed algorithm is feasible and efficient.
Fundamental solution of the problem of linear programming and method of its determination
NASA Technical Reports Server (NTRS)
Petrunin, S. V.
1978-01-01
The idea of a fundamental solution to a problem in linear programming is introduced. A method of determining the fundamental solution and of applying this method to the solution of a problem in linear programming is proposed. Numerical examples are cited.
NASA Astrophysics Data System (ADS)
Vasant, P.; Ganesan, T.; Elamvazuthi, I.
2012-11-01
A fairly reasonable result was obtained for non-linear engineering problems using the optimization techniques such as neural network, genetic algorithms, and fuzzy logic independently in the past. Increasingly, hybrid techniques are being used to solve the non-linear problems to obtain better output. This paper discusses the use of neuro-genetic hybrid technique to optimize the geological structure mapping which is known as seismic survey. It involves the minimization of objective function subject to the requirement of geophysical and operational constraints. In this work, the optimization was initially performed using genetic programming, and followed by hybrid neuro-genetic programming approaches. Comparative studies and analysis were then carried out on the optimized results. The results indicate that the hybrid neuro-genetic hybrid technique produced better results compared to the stand-alone genetic programming method.
NASA Astrophysics Data System (ADS)
Zhadan, V. G.
2016-07-01
The linear semidefinite programming problem is considered. The dual affine scaling method in which all current iterations belong to the feasible set is proposed for its solution. Moreover, the boundaries of the feasible set may be reached. This method is a generalization of a version of the affine scaling method that was earlier developed for linear programs to the case of semidefinite programming.
LP Relaxation of the Potts Labeling Problem Is as Hard as any Linear Program.
Prusa, Daniel; Werner, Tomas
2016-06-20
In our recent work, we showed that solving the LP relaxation of the pairwise min-sum labeling problem (also known as MAP inference in graphical models or discrete energy minimization) is not much easier than solving any linear program. Precisely, the general linear program reduces in linear time (assuming the Turing model of computation) to the LP relaxation of the min-sum labeling problem. The reduction is possible, though in quadratic time, even to the min-sum labeling problem with planar structure. Here we prove similar results for the pairwise minsum labeling problem with attractive Potts interactions (also known as the uniform metric labeling problem).
Bruhn, Peter; Geyer-Schulz, Andreas
2002-01-01
In this paper, we introduce genetic programming over context-free languages with linear constraints for combinatorial optimization, apply this method to several variants of the multidimensional knapsack problem, and discuss its performance relative to Michalewicz's genetic algorithm with penalty functions. With respect to Michalewicz's approach, we demonstrate that genetic programming over context-free languages with linear constraints improves convergence. A final result is that genetic programming over context-free languages with linear constraints is ideally suited to modeling complementarities between items in a knapsack problem: The more complementarities in the problem, the stronger the performance in comparison to its competitors.
LINOPT: A FORTRAN Routine for Solving Linear Programming Problems,
1981-10-09
MD 20910 2R44EA501 I I. CONTROLLING OFFICE NAME ANO AOORESS 12. REPORT DATE 9 October 1981 ’I. NUMBER OF PAGES 46 11. MONITORING AGENCY NAME...block /XXXLP/, which must accordingly be a common block in the calling program. ROUNDOFF CONTROL In the program there are three input variables which...can be used to control roundoff error accummulations. EPS is a tolerance used in checking constraint violations. H is also used to zero out
A New Bound for the Ration Between the 2-Matching Problem and Its Linear Programming Relaxation
Boyd, Sylvia; Carr, Robert
1999-07-28
Consider the 2-matching problem defined on the complete graph, with edge costs which satisfy the triangle inequality. We prove that the value of a minimum cost 2-matching is bounded above by 4/3 times the value of its linear programming relaxation, the fractional 2-matching problem. This lends credibility to a long-standing conjecture that the optimal value for the traveling salesman problem is bounded above by 4/3 times the value of its linear programming relaxation, the subtour elimination problem.
Zörnig, Peter
2015-08-01
We present integer programming models for some variants of the farthest string problem. The number of variables and constraints is substantially less than that of the integer linear programming models known in the literature. Moreover, the solution of the linear programming-relaxation contains only a small proportion of noninteger values, which considerably simplifies the rounding process. Numerical tests have shown excellent results, especially when a small set of long sequences is given.
NASA Technical Reports Server (NTRS)
Tuey, R. C.
1972-01-01
Computer solutions of linear programming problems are outlined. Information covers vector spaces, convex sets, and matrix algebra elements for solving simultaneous linear equations. Dual problems, reduced cost analysis, ranges, and error analysis are illustrated.
An application of a linear programing technique to nonlinear minimax problems
NASA Technical Reports Server (NTRS)
Schiess, J. R.
1973-01-01
A differential correction technique for solving nonlinear minimax problems is presented. The basis of the technique is a linear programing algorithm which solves the linear minimax problem. By linearizing the original nonlinear equations about a nominal solution, both nonlinear approximation and estimation problems using the minimax norm may be solved iteratively. Some consideration is also given to improving convergence and to the treatment of problems with more than one measured quantity. A sample problem is treated with this technique and with the least-squares differential correction method to illustrate the properties of the minimax solution. The results indicate that for the sample approximation problem, the minimax technique provides better estimates than the least-squares method if a sufficient amount of data is used. For the sample estimation problem, the minimax estimates are better if the mathematical model is incomplete.
A new neural network model for solving random interval linear programming problems.
Arjmandzadeh, Ziba; Safi, Mohammadreza; Nazemi, Alireza
2017-05-01
This paper presents a neural network model for solving random interval linear programming problems. The original problem involving random interval variable coefficients is first transformed into an equivalent convex second order cone programming problem. A neural network model is then constructed for solving the obtained convex second order cone problem. Employing Lyapunov function approach, it is also shown that the proposed neural network model is stable in the sense of Lyapunov and it is globally convergent to an exact satisfactory solution of the original problem. Several illustrative examples are solved in support of this technique.
Digital program for solving the linear stochastic optimal control and estimation problem
NASA Technical Reports Server (NTRS)
Geyser, L. C.; Lehtinen, B.
1975-01-01
A computer program is described which solves the linear stochastic optimal control and estimation (LSOCE) problem by using a time-domain formulation. The LSOCE problem is defined as that of designing controls for a linear time-invariant system which is disturbed by white noise in such a way as to minimize a performance index which is quadratic in state and control variables. The LSOCE problem and solution are outlined; brief descriptions are given of the solution algorithms, and complete descriptions of each subroutine, including usage information and digital listings, are provided. A test case is included, as well as information on the IBM 7090-7094 DCS time and storage requirements.
Visual, Algebraic and Mixed Strategies in Visually Presented Linear Programming Problems.
ERIC Educational Resources Information Center
Shama, Gilli; Dreyfus, Tommy
1994-01-01
Identified and classified solution strategies of (n=49) 10th-grade students who were presented with linear programming problems in a predominantly visual setting in the form of a computerized game. Visual strategies were developed more frequently than either algebraic or mixed strategies. Appendix includes questionnaires. (Contains 11 references.)…
Averaging and Linear Programming in Some Singularly Perturbed Problems of Optimal Control
Gaitsgory, Vladimir; Rossomakhine, Sergey
2015-04-15
The paper aims at the development of an apparatus for analysis and construction of near optimal solutions of singularly perturbed (SP) optimal controls problems (that is, problems of optimal control of SP systems) considered on the infinite time horizon. We mostly focus on problems with time discounting criteria but a possibility of the extension of results to periodic optimization problems is discussed as well. Our consideration is based on earlier results on averaging of SP control systems and on linear programming formulations of optimal control problems. The idea that we exploit is to first asymptotically approximate a given problem of optimal control of the SP system by a certain averaged optimal control problem, then reformulate this averaged problem as an infinite-dimensional linear programming (LP) problem, and then approximate the latter by semi-infinite LP problems. We show that the optimal solution of these semi-infinite LP problems and their duals (that can be found with the help of a modification of an available LP software) allow one to construct near optimal controls of the SP system. We demonstrate the construction with two numerical examples.
A strictly improving linear programming alorithm based on a series of Phase 1 problems
Leichner, S.A.; Dantzig, G.B.; Davis, J.W.
1992-04-01
When used on degenerate problems, the simplex method often takes a number of degenerate steps at a particular vertex before moving to the next. In theory (although rarely in practice), the simplex method can actually cycle at such a degenerate point. Instead of trying to modify the simplex method to avoid degenerate steps, we have developed a new linear programming algorithm that is completely impervious to degeneracy. This new method solves the Phase II problem of finding an optimal solution by solving a series of Phase I feasibility problems. Strict improvement is attained at each iteration in the Phase I algorithm, and the Phase II sequence of feasibility problems has linear convergence in the number of Phase I problems. When tested on the 30 smallest NETLIB linear programming test problems, the computational results for the new Phase II algorithm were over 15% faster than the simplex method; on some problems, it was almost two times faster, and on one problem it was four times faster.
IESIP - AN IMPROVED EXPLORATORY SEARCH TECHNIQUE FOR PURE INTEGER LINEAR PROGRAMMING PROBLEMS
NASA Technical Reports Server (NTRS)
Fogle, F. R.
1994-01-01
IESIP, an Improved Exploratory Search Technique for Pure Integer Linear Programming Problems, addresses the problem of optimizing an objective function of one or more variables subject to a set of confining functions or constraints by a method called discrete optimization or integer programming. Integer programming is based on a specific form of the general linear programming problem in which all variables in the objective function and all variables in the constraints are integers. While more difficult, integer programming is required for accuracy when modeling systems with small numbers of components such as the distribution of goods, machine scheduling, and production scheduling. IESIP establishes a new methodology for solving pure integer programming problems by utilizing a modified version of the univariate exploratory move developed by Robert Hooke and T.A. Jeeves. IESIP also takes some of its technique from the greedy procedure and the idea of unit neighborhoods. A rounding scheme uses the continuous solution found by traditional methods (simplex or other suitable technique) and creates a feasible integer starting point. The Hook and Jeeves exploratory search is modified to accommodate integers and constraints and is then employed to determine an optimal integer solution from the feasible starting solution. The user-friendly IESIP allows for rapid solution of problems up to 10 variables in size (limited by DOS allocation). Sample problems compare IESIP solutions with the traditional branch-and-bound approach. IESIP is written in Borland's TURBO Pascal for IBM PC series computers and compatibles running DOS. Source code and an executable are provided. The main memory requirement for execution is 25K. This program is available on a 5.25 inch 360K MS DOS format diskette. IESIP was developed in 1990. IBM is a trademark of International Business Machines. TURBO Pascal is registered by Borland International.
IESIP - AN IMPROVED EXPLORATORY SEARCH TECHNIQUE FOR PURE INTEGER LINEAR PROGRAMMING PROBLEMS
NASA Technical Reports Server (NTRS)
Fogle, F. R.
1994-01-01
IESIP, an Improved Exploratory Search Technique for Pure Integer Linear Programming Problems, addresses the problem of optimizing an objective function of one or more variables subject to a set of confining functions or constraints by a method called discrete optimization or integer programming. Integer programming is based on a specific form of the general linear programming problem in which all variables in the objective function and all variables in the constraints are integers. While more difficult, integer programming is required for accuracy when modeling systems with small numbers of components such as the distribution of goods, machine scheduling, and production scheduling. IESIP establishes a new methodology for solving pure integer programming problems by utilizing a modified version of the univariate exploratory move developed by Robert Hooke and T.A. Jeeves. IESIP also takes some of its technique from the greedy procedure and the idea of unit neighborhoods. A rounding scheme uses the continuous solution found by traditional methods (simplex or other suitable technique) and creates a feasible integer starting point. The Hook and Jeeves exploratory search is modified to accommodate integers and constraints and is then employed to determine an optimal integer solution from the feasible starting solution. The user-friendly IESIP allows for rapid solution of problems up to 10 variables in size (limited by DOS allocation). Sample problems compare IESIP solutions with the traditional branch-and-bound approach. IESIP is written in Borland's TURBO Pascal for IBM PC series computers and compatibles running DOS. Source code and an executable are provided. The main memory requirement for execution is 25K. This program is available on a 5.25 inch 360K MS DOS format diskette. IESIP was developed in 1990. IBM is a trademark of International Business Machines. TURBO Pascal is registered by Borland International.
Stable computation of search directions for near-degenerate linear programming problems
Hough, P.D.
1997-03-01
In this paper, we examine stability issues that arise when computing search directions ({delta}x, {delta}y, {delta} s) for a primal-dual path-following interior point method for linear programming. The dual step {delta}y can be obtained by solving a weighted least-squares problem for which the weight matrix becomes extremely il conditioned near the boundary of the feasible region. Hough and Vavisis proposed using a type of complete orthogonal decomposition (the COD algorithm) to solve such a problem and presented stability results. The work presented here addresses the stable computation of the primal step {delta}x and the change in the dual slacks {delta}s. These directions can be obtained in a straight-forward manner, but near-degeneracy in the linear programming instance introduces ill-conditioning which can cause numerical problems in this approach. Therefore, we propose a new method of computing {delta}x and {delta}s. More specifically, this paper describes and orthogonal projection algorithm that extends the COD method. Unlike other algorithms, this method is stable for interior point methods without assuming nondegeneracy in the linear programming instance. Thus, it is more general than other algorithms on near-degenerate problems.
A new gradient-based neural network for solving linear and quadratic programming problems.
Leung, Y; Chen, K Z; Jiao, Y C; Gao, X B; Leung, K S
2001-01-01
A new gradient-based neural network is constructed on the basis of the duality theory, optimization theory, convex analysis theory, Lyapunov stability theory, and LaSalle invariance principle to solve linear and quadratic programming problems. In particular, a new function F(x, y) is introduced into the energy function E(x, y) such that the function E(x, y) is convex and differentiable, and the resulting network is more efficient. This network involves all the relevant necessary and sufficient optimality conditions for convex quadratic programming problems. For linear programming and quadratic programming (QP) problems with unique and infinite number of solutions, we have proven strictly that for any initial point, every trajectory of the neural network converges to an optimal solution of the QP and its dual problem. The proposed network is different from the existing networks which use the penalty method or Lagrange method, and the inequality constraints are properly handled. The simulation results show that the proposed neural network is feasible and efficient.
The solution of the optimization problem of small energy complexes using linear programming methods
NASA Astrophysics Data System (ADS)
Ivanin, O. A.; Director, L. B.
2016-11-01
Linear programming methods were used for solving the optimization problem of schemes and operation modes of distributed generation energy complexes. Applicability conditions of simplex method, applied to energy complexes, including installations of renewable energy (solar, wind), diesel-generators and energy storage, considered. The analysis of decomposition algorithms for various schemes of energy complexes was made. The results of optimization calculations for energy complexes, operated autonomously and as a part of distribution grid, are presented.
Solving and analyzing side-chain positioning problems using linear and integer programming.
Kingsford, Carleton L; Chazelle, Bernard; Singh, Mona
2005-04-01
Side-chain positioning is a central component of homology modeling and protein design. In a common formulation of the problem, the backbone is fixed, side-chain conformations come from a rotamer library, and a pairwise energy function is optimized. It is NP-complete to find even a reasonable approximate solution to this problem. We seek to put this hardness result into practical context. We present an integer linear programming (ILP) formulation of side-chain positioning that allows us to tackle large problem sizes. We relax the integrality constraint to give a polynomial-time linear programming (LP) heuristic. We apply LP to position side chains on native and homologous backbones and to choose side chains for protein design. Surprisingly, when positioning side chains on native and homologous backbones, optimal solutions using a simple, biologically relevant energy function can usually be found using LP. On the other hand, the design problem often cannot be solved using LP directly; however, optimal solutions for large instances can still be found using the computationally more expensive ILP procedure. While different energy functions also affect the difficulty of the problem, the LP/ILP approach is able to find optimal solutions. Our analysis is the first large-scale demonstration that LP-based approaches are highly effective in finding optimal (and successive near-optimal) solutions for the side-chain positioning problem.
Observations on the linear programming formulation of the single reflector design problem.
Canavesi, Cristina; Cassarly, William J; Rolland, Jannick P
2012-02-13
We implemented the linear programming approach proposed by Oliker and by Wang to solve the single reflector problem for a point source and a far-field target. The algorithm was shown to produce solutions that aim the input rays at the intersections between neighboring reflectors. This feature makes it possible to obtain the same reflector with a low number of rays - of the order of the number of targets - as with a high number of rays, greatly reducing the computation complexity of the problem.
A novel approach based on preference-based index for interval bilevel linear programming problem.
Ren, Aihong; Wang, Yuping; Xue, Xingsi
2017-01-01
This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrained programming. With the consideration of different preferences of different decision makers, the concept of the preference level that the interval objective function is preferred to a target interval is defined based on the preference-based index. Then a preference-based deterministic bilevel programming problem is constructed in terms of the preference level and the order relation [Formula: see text]. Furthermore, the concept of a preference δ-optimal solution is given. Subsequently, the constructed deterministic nonlinear bilevel problem is solved with the help of estimation of distribution algorithm. Finally, several numerical examples are provided to demonstrate the effectiveness of the proposed approach.
APPLICATION OF LINEAR PROGRAMMING TO FACILITY MAINTENANCE PROBLEMS IN THE NAVY SHORE ESTABLISHMENT.
LINEAR PROGRAMMING ), (*NAVAL SHORE FACILITIES, MAINTENANCE), (*MAINTENANCE, COSTS, MATHEMATICAL MODELS, MANAGEMENT PLANNING AND CONTROL, MANPOWER, FEASIBILITY STUDIES, OPTIMIZATION, MANAGEMENT ENGINEERING.
Takabe, Satoshi; Hukushima, Koji
2016-05-01
Typical behavior of the linear programming (LP) problem is studied as a relaxation of the minimum vertex cover (min-VC), a type of integer programming (IP) problem. A lattice-gas model on the Erdös-Rényi random graphs of α-uniform hyperedges is proposed to express both the LP and IP problems of the min-VC in the common statistical mechanical model with a one-parameter family. Statistical mechanical analyses reveal for α=2 that the LP optimal solution is typically equal to that given by the IP below the critical average degree c=e in the thermodynamic limit. The critical threshold for good accuracy of the relaxation extends the mathematical result c=1 and coincides with the replica symmetry-breaking threshold of the IP. The LP relaxation for the minimum hitting sets with α≥3, minimum vertex covers on α-uniform random graphs, is also studied. Analytic and numerical results strongly suggest that the LP relaxation fails to estimate optimal values above the critical average degree c=e/(α-1) where the replica symmetry is broken.
NASA Astrophysics Data System (ADS)
Takabe, Satoshi; Hukushima, Koji
2016-05-01
Typical behavior of the linear programming (LP) problem is studied as a relaxation of the minimum vertex cover (min-VC), a type of integer programming (IP) problem. A lattice-gas model on the Erdös-Rényi random graphs of α -uniform hyperedges is proposed to express both the LP and IP problems of the min-VC in the common statistical mechanical model with a one-parameter family. Statistical mechanical analyses reveal for α =2 that the LP optimal solution is typically equal to that given by the IP below the critical average degree c =e in the thermodynamic limit. The critical threshold for good accuracy of the relaxation extends the mathematical result c =1 and coincides with the replica symmetry-breaking threshold of the IP. The LP relaxation for the minimum hitting sets with α ≥3 , minimum vertex covers on α -uniform random graphs, is also studied. Analytic and numerical results strongly suggest that the LP relaxation fails to estimate optimal values above the critical average degree c =e /(α -1 ) where the replica symmetry is broken.
An improved exploratory search technique for pure integer linear programming problems
NASA Technical Reports Server (NTRS)
Fogle, F. R.
1990-01-01
The development is documented of a heuristic method for the solution of pure integer linear programming problems. The procedure draws its methodology from the ideas of Hooke and Jeeves type 1 and 2 exploratory searches, greedy procedures, and neighborhood searches. It uses an efficient rounding method to obtain its first feasible integer point from the optimal continuous solution obtained via the simplex method. Since this method is based entirely on simple addition or subtraction of one to each variable of a point in n-space and the subsequent comparison of candidate solutions to a given set of constraints, it facilitates significant complexity improvements over existing techniques. It also obtains the same optimal solution found by the branch-and-bound technique in 44 of 45 small to moderate size test problems. Two example problems are worked in detail to show the inner workings of the method. Furthermore, using an established weighted scheme for comparing computational effort involved in an algorithm, a comparison of this algorithm is made to the more established and rigorous branch-and-bound method. A computer implementation of the procedure, in PC compatible Pascal, is also presented and discussed.
Method of expanding hyperspheres - an interior algorithm for linear programming problems
Chandrupatla, T.
1994-12-31
A new interior algorithm using some properties of hyperspheres is proposed for the solution of linear programming problems with inequality constraints: maximize c{sup T} x subject to Ax {<=} b where c and rows of A are normalized in the Euclidean sense such that {parallel} c {parallel} = {radical}c{sup T}c = 1 {parallel} a{sub i} {parallel} {radical} A{sub i}A{sub i}{sup T} = 1 for i = 1 to m. The feasible region in the polytope bounded by the constraint planes. We start from an interior point. We pass a plane normal to c until it touches a constraint plane. Then the sphere is expanded so that it keeps contact with the previously touched planes and the expansion proceeds till it touches another plane. The procedure is continued till the sphere touches the c-plane and n constraint planes. We move to the center of the sphere and repeat the process. The interior maximum is reached when the radius of the expanded sphere is less than a critical value say {epsilon}. Problems of direction finding, determination of incoming constraint, sphere jamming, and evaluation of the initial feasible point are discussed.
Wu, Z; Zhang, Y
2008-01-01
The double digestion problem for DNA restriction mapping has been proved to be NP-complete and intractable if the numbers of the DNA fragments become large. Several approaches to the problem have been tested and proved to be effective only for small problems. In this paper, we formulate the problem as a mixed-integer linear program (MIP) by following (Waterman, 1995) in a slightly different form. With this formulation and using state-of-the-art integer programming techniques, we can solve randomly generated problems whose search space sizes are many-magnitude larger than previously reported testing sizes.
Error Analysis Of Students Working About Word Problem Of Linear Program With NEA Procedure
NASA Astrophysics Data System (ADS)
Santoso, D. A.; Farid, A.; Ulum, B.
2017-06-01
Evaluation and assessment is an important part of learning. In evaluation process of learning, written test is still commonly used. However, the tests usually do not following-up by further evaluation. The process only up to grading stage not to evaluate the process and errors which done by students. Whereas if the student has a pattern error and process error, actions taken can be more focused on the fault and why is that happen. NEA procedure provides a way for educators to evaluate student progress more comprehensively. In this study, students’ mistakes in working on some word problem about linear programming have been analyzed. As a result, mistakes are often made students exist in the modeling phase (transformation) and process skills (process skill) with the overall percentage distribution respectively 20% and 15%. According to the observations, these errors occur most commonly due to lack of precision of students in modeling and in hastiness calculation. Error analysis with students on this matter, it is expected educators can determine or use the right way to solve it in the next lesson.
A Mixed Integer Linear Program for Solving a Multiple Route Taxi Scheduling Problem
NASA Technical Reports Server (NTRS)
Montoya, Justin Vincent; Wood, Zachary Paul; Rathinam, Sivakumar; Malik, Waqar Ahmad
2010-01-01
Aircraft movements on taxiways at busy airports often create bottlenecks. This paper introduces a mixed integer linear program to solve a Multiple Route Aircraft Taxi Scheduling Problem. The outputs of the model are in the form of optimal taxi schedules, which include routing decisions for taxiing aircraft. The model extends an existing single route formulation to include routing decisions. An efficient comparison framework compares the multi-route formulation and the single route formulation. The multi-route model is exercised for east side airport surface traffic at Dallas/Fort Worth International Airport to determine if any arrival taxi time savings can be achieved by allowing arrivals to have two taxi routes: a route that crosses an active departure runway and a perimeter route that avoids the crossing. Results indicate that the multi-route formulation yields reduced arrival taxi times over the single route formulation only when a perimeter taxiway is used. In conditions where the departure aircraft are given an optimal and fixed takeoff sequence, accumulative arrival taxi time savings in the multi-route formulation can be as high as 3.6 hours more than the single route formulation. If the departure sequence is not optimal, the multi-route formulation results in less taxi time savings made over the single route formulation, but the average arrival taxi time is significantly decreased.
NASA Technical Reports Server (NTRS)
Young, Katherine C.; Sobieszczanski-Sobieski, Jaroslaw
1988-01-01
This project has two objectives. The first is to determine whether linear programming techniques can improve performance when handling design optimization problems with a large number of design variables and constraints relative to the feasible directions algorithm. The second purpose is to determine whether using the Kreisselmeier-Steinhauser (KS) function to replace the constraints with one constraint will reduce the cost of total optimization. Comparisons are made using solutions obtained with linear and non-linear methods. The results indicate that there is no cost saving using the linear method or in using the KS function to replace constraints.
Sparse linear programming subprogram
Hanson, R.J.; Hiebert, K.L.
1981-12-01
This report describes a subprogram, SPLP(), for solving linear programming problems. The package of subprogram units comprising SPLP() is written in Fortran 77. The subprogram SPLP() is intended for problems involving at most a few thousand constraints and variables. The subprograms are written to take advantage of sparsity in the constraint matrix. A very general problem statement is accepted by SPLP(). It allows upper, lower, or no bounds on the variables. Both the primal and dual solutions are returned as output parameters. The package has many optional features. Among them is the ability to save partial results and then use them to continue the computation at a later time.
1987-05-01
Laboratory •U The Equivmluce of Dentig’$ Self-Dual Parametric Algorithm for Linemr Progame to Lems Ngorithm fur Lse Cemllusemtawt Problems Appled to Umer...agement Science 11, pp. 681-689. Lemke, C.E. (1970). "Recent results on complementarity problems," in Nonlinear pro- gramming (J.B. Rosen, O.L
NASA Technical Reports Server (NTRS)
Ferencz, Donald C.; Viterna, Larry A.
1991-01-01
ALPS is a computer program which can be used to solve general linear program (optimization) problems. ALPS was designed for those who have minimal linear programming (LP) knowledge and features a menu-driven scheme to guide the user through the process of creating and solving LP formulations. Once created, the problems can be edited and stored in standard DOS ASCII files to provide portability to various word processors or even other linear programming packages. Unlike many math-oriented LP solvers, ALPS contains an LP parser that reads through the LP formulation and reports several types of errors to the user. ALPS provides a large amount of solution data which is often useful in problem solving. In addition to pure linear programs, ALPS can solve for integer, mixed integer, and binary type problems. Pure linear programs are solved with the revised simplex method. Integer or mixed integer programs are solved initially with the revised simplex, and the completed using the branch-and-bound technique. Binary programs are solved with the method of implicit enumeration. This manual describes how to use ALPS to create, edit, and solve linear programming problems. Instructions for installing ALPS on a PC compatible computer are included in the appendices along with a general introduction to linear programming. A programmers guide is also included for assistance in modifying and maintaining the program.
Fan, Yurui; Huang, Guohe; Veawab, Amornvadee
2012-01-01
In this study, a generalized fuzzy linear programming (GFLP) method was developed to deal with uncertainties expressed as fuzzy sets that exist in the constraints and objective function. A stepwise interactive algorithm (SIA) was advanced to solve GFLP model and generate solutions expressed as fuzzy sets. To demonstrate its application, the developed GFLP method was applied to a regional sulfur dioxide (SO2) control planning model to identify effective SO2 mitigation polices with a minimized system performance cost under uncertainty. The results were obtained to represent the amount of SO2 allocated to different control measures from different sources. Compared with the conventional interval-parameter linear programming (ILP) approach, the solutions obtained through GFLP were expressed as fuzzy sets, which can provide intervals for the decision variables and objective function, as well as related possibilities. Therefore, the decision makers can make a tradeoff between model stability and the plausibility based on solutions obtained through GFLP and then identify desired policies for SO2-emission control under uncertainty.
NASA Astrophysics Data System (ADS)
Ebrahimnejad, Ali
2015-08-01
There are several methods, in the literature, for solving fuzzy variable linear programming problems (fuzzy linear programming in which the right-hand-side vectors and decision variables are represented by trapezoidal fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings a new method based on the bounded dual simplex method is proposed to determine the fuzzy optimal solution of that kind of fuzzy variable linear programming problems in which some or all variables are restricted to lie within lower and upper bounds. To illustrate the proposed method, an application example is solved and the obtained results are given. The advantages of the proposed method over existing methods are discussed. Also, one application of this algorithm in solving bounded transportation problems with fuzzy supplies and demands is dealt with. The proposed method is easy to understand and to apply for determining the fuzzy optimal solution of bounded fuzzy variable linear programming problems occurring in real-life situations.
Linear Programming across the Curriculum
ERIC Educational Resources Information Center
Yoder, S. Elizabeth; Kurz, M. Elizabeth
2015-01-01
Linear programming (LP) is taught in different departments across college campuses with engineering and management curricula. Modeling an LP problem is taught in every linear programming class. As faculty teaching in Engineering and Management departments, the depth to which teachers should expect students to master this particular type of…
Linear Programming across the Curriculum
ERIC Educational Resources Information Center
Yoder, S. Elizabeth; Kurz, M. Elizabeth
2015-01-01
Linear programming (LP) is taught in different departments across college campuses with engineering and management curricula. Modeling an LP problem is taught in every linear programming class. As faculty teaching in Engineering and Management departments, the depth to which teachers should expect students to master this particular type of…
Fernandes, L.; Friedlander, A.; Guedes, M.; Judice, J.
2001-07-01
This paper addresses a General Linear Complementarity Problem (GLCP) that has found applications in global optimization. It is shown that a solution of the GLCP can be computed by finding a stationary point of a differentiable function over a set defined by simple bounds on the variables. The application of this result to the solution of bilinear programs and LCPs is discussed. Some computational evidence of its usefulness is included in the last part of the paper.
NASA Astrophysics Data System (ADS)
Noor-E-Alam, Md.; Doucette, John
2015-08-01
Grid-based location problems (GBLPs) can be used to solve location problems in business, engineering, resource exploitation, and even in the field of medical sciences. To solve these decision problems, an integer linear programming (ILP) model is designed and developed to provide the optimal solution for GBLPs considering fixed cost criteria. Preliminary results show that the ILP model is efficient in solving small to moderate-sized problems. However, this ILP model becomes intractable in solving large-scale instances. Therefore, a decomposition heuristic is proposed to solve these large-scale GBLPs, which demonstrates significant reduction of solution runtimes. To benchmark the proposed heuristic, results are compared with the exact solution via ILP. The experimental results show that the proposed method significantly outperforms the exact method in runtime with minimal (and in most cases, no) loss of optimality.
NASA Technical Reports Server (NTRS)
Lawson, C. L.; Krogh, F. T.; Gold, S. S.; Kincaid, D. R.; Sullivan, J.; Williams, E.; Hanson, R. J.; Haskell, K.; Dongarra, J.; Moler, C. B.
1982-01-01
The Basic Linear Algebra Subprograms (BLAS) library is a collection of 38 FORTRAN-callable routines for performing basic operations of numerical linear algebra. BLAS library is portable and efficient source of basic operations for designers of programs involving linear algebriac computations. BLAS library is supplied in portable FORTRAN and Assembler code versions for IBM 370, UNIVAC 1100 and CDC 6000 series computers.
NASA Technical Reports Server (NTRS)
Lawson, C. L.; Krogh, F. T.; Gold, S. S.; Kincaid, D. R.; Sullivan, J.; Williams, E.; Hanson, R. J.; Haskell, K.; Dongarra, J.; Moler, C. B.
1982-01-01
The Basic Linear Algebra Subprograms (BLAS) library is a collection of 38 FORTRAN-callable routines for performing basic operations of numerical linear algebra. BLAS library is portable and efficient source of basic operations for designers of programs involving linear algebriac computations. BLAS library is supplied in portable FORTRAN and Assembler code versions for IBM 370, UNIVAC 1100 and CDC 6000 series computers.
NASA Technical Reports Server (NTRS)
Utku, S.
1969-01-01
A general purpose digital computer program for the in-core solution of linear equilibrium problems of structural mechanics is documented. The program requires minimum input for the description of the problem. The solution is obtained by means of the displacement method and the finite element technique. Almost any geometry and structure may be handled because of the availability of linear, triangular, quadrilateral, tetrahedral, hexahedral, conical, triangular torus, and quadrilateral torus elements. The assumption of piecewise linear deflection distribution insures monotonic convergence of the deflections from the stiffer side with decreasing mesh size. The stresses are provided by the best-fit strain tensors in the least squares at the mesh points where the deflections are given. The selection of local coordinate systems whenever necessary is automatic. The core memory is used by means of dynamic memory allocation, an optional mesh-point relabelling scheme and imposition of the boundary conditions during the assembly time.
ERIC Educational Resources Information Center
Sole, Marla A.
2016-01-01
Open-ended questions that can be solved using different strategies help students learn and integrate content, and provide teachers with greater insights into students' unique capabilities and levels of understanding. This article provides a problem that was modified to allow for multiple approaches. Students tended to employ high-powered, complex,…
ERIC Educational Resources Information Center
Sole, Marla A.
2016-01-01
Open-ended questions that can be solved using different strategies help students learn and integrate content, and provide teachers with greater insights into students' unique capabilities and levels of understanding. This article provides a problem that was modified to allow for multiple approaches. Students tended to employ high-powered, complex,…
Can linear superiorization be useful for linear optimization problems?
NASA Astrophysics Data System (ADS)
Censor, Yair
2017-04-01
Linear superiorization (LinSup) considers linear programming problems but instead of attempting to solve them with linear optimization methods it employs perturbation resilient feasibility-seeking algorithms and steers them toward reduced (not necessarily minimal) target function values. The two questions that we set out to explore experimentally are: (i) does LinSup provide a feasible point whose linear target function value is lower than that obtained by running the same feasibility-seeking algorithm without superiorization under identical conditions? (ii) How does LinSup fare in comparison with the Simplex method for solving linear programming problems? Based on our computational experiments presented here, the answers to these two questions are: ‘yes’ and ‘very well’, respectively.
On the linear programming bound for linear Lee codes.
Astola, Helena; Tabus, Ioan
2016-01-01
Based on an invariance-type property of the Lee-compositions of a linear Lee code, additional equality constraints can be introduced to the linear programming problem of linear Lee codes. In this paper, we formulate this property in terms of an action of the multiplicative group of the field [Formula: see text] on the set of Lee-compositions. We show some useful properties of certain sums of Lee-numbers, which are the eigenvalues of the Lee association scheme, appearing in the linear programming problem of linear Lee codes. Using the additional equality constraints, we formulate the linear programming problem of linear Lee codes in a very compact form, leading to a fast execution, which allows to efficiently compute the bounds for large parameter values of the linear codes.
The linear separability problem: some testing methods.
Elizondo, D
2006-03-01
The notion of linear separability is used widely in machine learning research. Learning algorithms that use this concept to learn include neural networks (single layer perceptron and recursive deterministic perceptron), and kernel machines (support vector machines). This paper presents an overview of several of the methods for testing linear separability between two classes. The methods are divided into four groups: Those based on linear programming, those based on computational geometry, one based on neural networks, and one based on quadratic programming. The Fisher linear discriminant method is also presented. A section on the quantification of the complexity of classification problems is included.
ERIC Educational Resources Information Center
Nakhanu, Shikuku Beatrice; Musasia, Amadalo Maurice
2015-01-01
The topic Linear Programming is included in the compulsory Kenyan secondary school mathematics curriculum at form four. The topic provides skills for determining best outcomes in a given mathematical model involving some linear relationship. This technique has found application in business, economics as well as various engineering fields. Yet many…
The report discusses a two person max -min problem in which the maximizing player moves first and the minimizing player has perfect information of the...The joint constraints as well as the objective function are assumed to be linear. For this problem it is shown that the familiar inequality min max ...or = max min is reversed due to the influence of the joint constraints. The problem is characterized as a nonconvex program and a method of
NASA Astrophysics Data System (ADS)
Karterakis, Stefanos M.; Karatzas, George P.; Nikolos, Ioannis K.; Papadopoulou, Maria P.
2007-09-01
SummaryIn the past optimization techniques have been combined with simulation models to determine cost-effective solutions for various environmental management problems. In the present study, a groundwater management problem in a coastal karstic aquifer in Crere, Greece subject to environmental criteria has been studied using classical linear programming and heuristic optimization methodologies. A numerical simulation model of the unconfined coastal aquifer has been first developed to represent the complex non-linear physical system. Then the classical linear programming optimization algorithm of the Simplex method is used to solve the groundwater management problem where the main objective is the hydraulic control of the saltwater intrusion. A piecewise linearization of the non-linear optimization problem is obtained by sequential implementation of the Simplex algorithm and a convergence to the optimal solution is achieved. The solution of the non-linear management problem is also obtained using a heuristic algorithm. A Differential Evolution (DE) algorithm that emulates some of the principles of evolution is used. A comparison of the results obtained by the two different optimization approaches is presented. Finally, a sensitivity analysis is employed in order to examine the influence of the active pumping wells in the evolution of the seawater intrusion front along the coastline.
ERIC Educational Resources Information Center
Mills, James W.; And Others
1973-01-01
The Study reported here tested an application of the Linear Programming Model at the Reading Clinic of Drew University. Results, while not conclusive, indicate that this approach yields greater gains in speed scores than a traditional approach for this population. (Author)
Linear stochastic optimal control and estimation problem
NASA Technical Reports Server (NTRS)
Geyser, L. C.; Lehtinen, F. K. B.
1980-01-01
Problem involves design of controls for linear time-invariant system disturbed by white noise. Solution is Kalman filter coupled through set of optimal regulator gains to produce desired control signal. Key to solution is solving matrix Riccati differential equation. LSOCE effectively solves problem for wide range of practical applications. Program is written in FORTRAN IV for batch execution and has been implemented on IBM 360.
1980-05-31
Multiconstraint Zero - One Knapsack Problem ," The Journal of the Operational Research Society, Vol. 30, 1979, pp. 369-378. 69 [41] Kepler, C...programming. Shih [401 has written on a branch and bound method , Kepler and Blackman [41] have demonstrated the use of dynamic programming in the selection of...Portfolio Selection Model," IEEE A. Transactions on Engineering Management, Vol. EM-26, No. 1, 1979, pp. 2-7. [40] Shih, Wei, "A Branch and
NASA Technical Reports Server (NTRS)
Klumpp, A. R.; Lawson, C. L.
1988-01-01
Routines provided for common scalar, vector, matrix, and quaternion operations. Computer program extends Ada programming language to include linear-algebra capabilities similar to HAS/S programming language. Designed for such avionics applications as software for Space Station.
Linearization problem in pseudolite surveys
NASA Astrophysics Data System (ADS)
Cellmer, Slawomir; Rapinski, Jacek
2010-06-01
GPS augmented with pseudolites (PL), can be used in various engineering surveys. Also pseudolite—only navigation system can be designed and used in any place, even if GPS signal is not available (Kee et al. Development of indoor navigation system using asynchronous pseudolites, 1038-1045, 2000). Especially in engineering surveys, where harsh survey environment is common, pseudolites have a lot of applications. Pseudolites may be used in construction sites, open pit mines, city canyons, GPS and PL baseline processing is similar, although there are few differences that must be taken into account. One of the major issues is linearization problem. The source of the problem is neglecting second terms of Taylor series expansion in GPS baseline processing software. This problem occurs when the pseudolite is relatively close to the receiver, which is the case in PL surveys. In this paper authors presents the algorithm for GPS + PL data processing including, neglected in classical GPS only approach, second terms of Taylor series expansion. The mathematical model of adjustment problem, detailed proposal of application in baseline processing algorithms, and numerical tests are presented.
A neural network for bounded linear programming
Culioli, J.C.; Protopopescu, V.; Britton, C.; Ericson, N. )
1989-01-01
The purpose of this paper is to describe a neural network implementation of an algorithm recently designed at ORNL to solve the Transportation and the Assignment Problems, and, more generally, any explicitly bounded linear program. 9 refs.
Portfolio optimization using fuzzy linear programming
NASA Astrophysics Data System (ADS)
Pandit, Purnima K.
2013-09-01
Portfolio Optimization (PO) is a problem in Finance, in which investor tries to maximize return and minimize risk by carefully choosing different assets. Expected return and risk are the most important parameters with regard to optimal portfolios. In the simple form PO can be modeled as quadratic programming problem which can be put into equivalent linear form. PO problems with the fuzzy parameters can be solved as multi-objective fuzzy linear programming problem. In this paper we give the solution to such problems with an illustrative example.
ALPS - A LINEAR PROGRAM SOLVER
NASA Technical Reports Server (NTRS)
Viterna, L. A.
1994-01-01
Linear programming is a widely-used engineering and management tool. Scheduling, resource allocation, and production planning are all well-known applications of linear programs (LP's). Most LP's are too large to be solved by hand, so over the decades many computer codes for solving LP's have been developed. ALPS, A Linear Program Solver, is a full-featured LP analysis program. ALPS can solve plain linear programs as well as more complicated mixed integer and pure integer programs. ALPS also contains an efficient solution technique for pure binary (0-1 integer) programs. One of the many weaknesses of LP solvers is the lack of interaction with the user. ALPS is a menu-driven program with no special commands or keywords to learn. In addition, ALPS contains a full-screen editor to enter and maintain the LP formulation. These formulations can be written to and read from plain ASCII files for portability. For those less experienced in LP formulation, ALPS contains a problem "parser" which checks the formulation for errors. ALPS creates fully formatted, readable reports that can be sent to a printer or output file. ALPS is written entirely in IBM's APL2/PC product, Version 1.01. The APL2 workspace containing all the ALPS code can be run on any APL2/PC system (AT or 386). On a 32-bit system, this configuration can take advantage of all extended memory. The user can also examine and modify the ALPS code. The APL2 workspace has also been "packed" to be run on any DOS system (without APL2) as a stand-alone "EXE" file, but has limited memory capacity on a 640K system. A numeric coprocessor (80X87) is optional but recommended. The standard distribution medium for ALPS is a 5.25 inch 360K MS-DOS format diskette. IBM, IBM PC and IBM APL2 are registered trademarks of International Business Machines Corporation. MS-DOS is a registered trademark of Microsoft Corporation.
Gadgets, approximation, and linear programming
Trevisan, L.; Sudan, M.; Sorkin, G.B.; Williamson, D.P.
1996-12-31
We present a linear-programming based method for finding {open_quotes}gadgets{close_quotes}, i.e., combinatorial structures reducing constraints of one optimization problems to constraints of another. A key step in this method is a simple observation which limits the search space to a finite one. Using this new method we present a number of new, computer-constructed gadgets for several different reductions. This method also answers a question posed by on how to prove the optimality of gadgets-we show how LP duality gives such proofs. The new gadgets improve hardness results for MAX CUT and MAX DICUT, showing that approximating these problems to within factors of 60/61 and 44/45 respectively is N P-hard. We also use the gadgets to obtain an improved approximation algorithm for MAX 3SAT which guarantees an approximation ratio of .801. This improves upon the previous best bound of .7704.
Evolving evolutionary algorithms using linear genetic programming.
Oltean, Mihai
2005-01-01
A new model for evolving Evolutionary Algorithms is proposed in this paper. The model is based on the Linear Genetic Programming (LGP) technique. Every LGP chromosome encodes an EA which is used for solving a particular problem. Several Evolutionary Algorithms for function optimization, the Traveling Salesman Problem and the Quadratic Assignment Problem are evolved by using the considered model. Numerical experiments show that the evolved Evolutionary Algorithms perform similarly and sometimes even better than standard approaches for several well-known benchmarking problems.
Generalised Assignment Matrix Methodology in Linear Programming
ERIC Educational Resources Information Center
Jerome, Lawrence
2012-01-01
Discrete Mathematics instructors and students have long been struggling with various labelling and scanning algorithms for solving many important problems. This paper shows how to solve a wide variety of Discrete Mathematics and OR problems using assignment matrices and linear programming, specifically using Excel Solvers although the same…
Generalised Assignment Matrix Methodology in Linear Programming
ERIC Educational Resources Information Center
Jerome, Lawrence
2012-01-01
Discrete Mathematics instructors and students have long been struggling with various labelling and scanning algorithms for solving many important problems. This paper shows how to solve a wide variety of Discrete Mathematics and OR problems using assignment matrices and linear programming, specifically using Excel Solvers although the same…
Linear Programming With Applications to Educational Planning.
ERIC Educational Resources Information Center
Carman, Robert A.
This document discusses the value of linear programing in finding minimum and maximum solutions to problems of resource allocation. Three models using this technique are given for the areas of educational finance, school district personnel compensation, and instructional program evaluation. (RA)
Stochastic Linear Quadratic Optimal Control Problems
Chen, S.; Yong, J.
2001-07-01
This paper is concerned with the stochastic linear quadratic optimal control problem (LQ problem, for short) for which the coefficients are allowed to be random and the cost functional is allowed to have a negative weight on the square of the control variable. Some intrinsic relations among the LQ problem, the stochastic maximum principle, and the (linear) forward-backward stochastic differential equations are established. Some results involving Riccati equation are discussed as well.
An Intuitive Approach in Teaching Linear Programming in High School.
ERIC Educational Resources Information Center
Ulep, Soledad A.
1990-01-01
Discusses solving inequality problems involving linear programing. Describes the usual and alternative approaches. Presents an intuitive approach for finding a feasible solution by maximizing the objective function. (YP)
Granja, C; Almada-Lobo, B; Janela, F; Seabra, J; Mendes, A
2014-12-01
As patient's length of stay in waiting lists increases, governments are looking for strategies to control the problem. Agreements were created with private providers to diminish the workload in the public sector. However, the growth of the private sector is not following the demand for care. Given this context, new management strategies have to be considered in order to minimize patient length of stay in waiting lists while reducing the costs and increasing (or at least maintaining) the quality of care. Appointment scheduling systems are today known to be proficient in the optimization of health care services. Their utilization is focused on increasing the usage of human resources, medical equipment and reducing the patient waiting times. In this paper, a simulation-based optimization approach to the Patient Admission Scheduling Problem is presented. Modeling tools and simulation techniques are used in the optimization of a diagnostic imaging department. The proposed techniques have demonstrated to be effective in the evaluation of diagnostic imaging workflows. A simulated annealing algorithm was used to optimize the patient admission sequence towards minimizing the total completion and total waiting of patients. The obtained results showed average reductions of 5% on the total completion and 38% on the patients' total waiting time. Copyright © 2014 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Park, Jae Woo
1996-06-01
The generalized linear impulsive correction problem is applied to make a linear programming problem for optimizing trajectory of an orbiting spacecraft. Numerical application for the stationkeeping maneuver problem of geostationary satellite shows that this problem can efficiently find the optimal solution of the stationkeeping parameters, such as velocity changes, and the points of impulse by using the revised simplex method.
Programming and Problem Solving.
ERIC Educational Resources Information Center
Elias, Barbara P.
A study was conducted to examine computer programming as a problem solving activity. Thirteen fifth grade children were selected by their teacher from an above average class to use Apple IIe microcomputers. The investigator conducted sessions of 40-50 minutes with the children in groups of two or three. Four problems, incorporating the programming…
Linear programming computational experience with onyx
Atrek, E.
1994-12-31
ONYX is a linear programming software package based on an efficient variation of the gradient projection method. When fully configured, it is intended for application to industrial size problems. While the computational experience is limited at the time of this abstract, the technique is found to be robust and competitive with existing methodology in terms of both accuracy and speed. An overview of the approach is presented together with a description of program capabilities, followed by a discussion of up-to-date computational experience with the program. Conclusions include advantages of the approach and envisioned future developments.
Linear System of Equations, Matrix Inversion, and Linear Programming Using MS Excel
ERIC Educational Resources Information Center
El-Gebeily, M.; Yushau, B.
2008-01-01
In this note, we demonstrate with illustrations two different ways that MS Excel can be used to solve Linear Systems of Equation, Linear Programming Problems, and Matrix Inversion Problems. The advantage of using MS Excel is its availability and transparency (the user is responsible for most of the details of how a problem is solved). Further, we…
Linear System of Equations, Matrix Inversion, and Linear Programming Using MS Excel
ERIC Educational Resources Information Center
El-Gebeily, M.; Yushau, B.
2008-01-01
In this note, we demonstrate with illustrations two different ways that MS Excel can be used to solve Linear Systems of Equation, Linear Programming Problems, and Matrix Inversion Problems. The advantage of using MS Excel is its availability and transparency (the user is responsible for most of the details of how a problem is solved). Further, we…
Singular linear-quadratic control problem for systems with linear delay
Sesekin, A. N.
2013-12-18
A singular linear-quadratic optimization problem on the trajectories of non-autonomous linear differential equations with linear delay is considered. The peculiarity of this problem is the fact that this problem has no solution in the class of integrable controls. To ensure the existence of solutions is required to expand the class of controls including controls with impulse components. Dynamical systems with linear delay are used to describe the motion of pantograph from the current collector with electric traction, biology, etc. It should be noted that for practical problems fact singularity criterion of quality is quite commonly occurring, and therefore the study of these problems is surely important. For the problem under discussion optimal programming control contained impulse components at the initial and final moments of time is constructed under certain assumptions on the functional and the right side of the control system.
The Vertical Linear Fractional Initialization Problem
NASA Technical Reports Server (NTRS)
Lorenzo, Carl F.; Hartley, Tom T.
1999-01-01
This paper presents a solution to the initialization problem for a system of linear fractional-order differential equations. The scalar problem is considered first, and solutions are obtained both generally and for a specific initialization. Next the vector fractional order differential equation is considered. In this case, the solution is obtained in the form of matrix F-functions. Some control implications of the vector case are discussed. The suggested method of problem solution is shown via an example.
A program for identification of linear systems
NASA Technical Reports Server (NTRS)
Buell, J.; Kalaba, R.; Ruspini, E.; Yakush, A.
1971-01-01
A program has been written for the identification of parameters in certain linear systems. These systems appear in biomedical problems, particularly in compartmental models of pharmacokinetics. The method presented here assumes that some of the state variables are regularly modified by jump conditions. This simulates administration of drugs following some prescribed drug regime. Parameters are identified by a least-square fit of the linear differential system to a set of experimental observations. The method is especially suited when the interval of observation of the system is very long.
Piecewise linear approximation for hereditary control problems
NASA Technical Reports Server (NTRS)
Propst, Georg
1990-01-01
This paper presents finite-dimensional approximations for linear retarded functional differential equations by use of discontinuous piecewise linear functions. The approximation scheme is applied to optimal control problems, when a quadratic cost integral must be minimized subject to the controlled retarded system. It is shown that the approximate optimal feedback operators converge to the true ones both in the case where the cost integral ranges over a finite time interval, as well as in the case where it ranges over an infinite time interval. The arguments in the last case rely on the fact that the piecewise linear approximations to stable systems are stable in a uniform sense.
New approaches to linear and nonlinear programming
Murray, W.; Saunders, M.A.
1990-03-01
During the last twelve months, research has concentrated on barrier- function methods for linear programming (LP) and quadratic programming (QP). Some ground-work for the application of barrier methods to nonlinearly constrained problems has also begun. In our previous progress report we drew attention to the difficulty of developing robust implementations of barrier methods for LP. We have continued to refine both the primal algorithm and the dual algorithm. We still do not claim that the barrier algorithms are as robust as the simplex method; however, the dual algorithm has solved all the problems in our extensive test set. We have also gained some experience with using the algorithms to solve aircrew scheduling problems.
Matching by linear programming and successive convexification.
Jiang, Hao; Drew, Mark S; Li, Ze-Nian
2007-06-01
We present a novel convex programming scheme to solve matching problems, focusing on the challenging problem of matching in a large search range and with cluttered background. Matching is formulated as metric labeling with L1 regularization terms, for which we propose a novel linear programming relaxation method and an efficient successive convexification implementation. The unique feature of the proposed relaxation scheme is that a much smaller set of basis labels is used to represent the original label space. This greatly reduces the size of the searching space. A successive convexification scheme solves the labeling problem in a coarse to fine manner. Importantly, the original cost function is reconvexified at each stage, in the new focus region only, and the focus region is updated so as to refine the searching result. This makes the method well-suited for large label set matching. Experiments demonstrate successful applications of the proposed matching scheme in object detection, motion estimation, and tracking.
The linear regulator problem for parabolic systems
NASA Technical Reports Server (NTRS)
Banks, H. T.; Kunisch, K.
1983-01-01
An approximation framework is presented for computation (in finite imensional spaces) of Riccati operators that can be guaranteed to converge to the Riccati operator in feedback controls for abstract evolution systems in a Hilbert space. It is shown how these results may be used in the linear optimal regulator problem for a large class of parabolic systems.
Dynamics of Kepler problem with linear drag
NASA Astrophysics Data System (ADS)
Margheri, Alessandro; Ortega, Rafael; Rebelo, Carlota
2014-09-01
We study the dynamics of Kepler problem with linear drag. We prove that motions with nonzero angular momentum have no collisions and travel from infinity to the singularity. In the process, the energy takes all real values and the angular velocity becomes unbounded. We also prove that there are two types of linear motions: capture-collision and ejection-collision. The behaviour of solutions at collisions is the same as in the conservative case. Proofs are obtained using the geometric theory of ordinary differential equations and two regularizations for the singularity of Kepler problem equation. The first, already considered in Diacu (Celest Mech Dyn Astron 75:1-15, 1999), is mainly used for the study of the linear motions. The second, the well known Levi-Civita transformation, allows to complete the study of the asymptotic values of the energy and to prove the existence of collision solutions with arbitrary energy.
Ranking Forestry Investments With Parametric Linear Programming
Paul A. Murphy
1976-01-01
Parametric linear programming is introduced as a technique for ranking forestry investments under multiple constraints; it combines the advantages of simple tanking and linear programming as capital budgeting tools.
Piecewise linear approximation for hereditary control problems
NASA Technical Reports Server (NTRS)
Propst, Georg
1987-01-01
Finite dimensional approximations are presented for linear retarded functional differential equations by use of discontinuous piecewise linear functions. The approximation scheme is applied to optimal control problems when a quadratic cost integral has to be minimized subject to the controlled retarded system. It is shown that the approximate optimal feedback operators converge to the true ones both in case the cost integral ranges over a finite time interval as well as in the case it ranges over an infinite time interval. The arguments in the latter case rely on the fact that the piecewise linear approximations to stable systems are stable in a uniform sense. This feature is established using a vector-component stability criterion in the state space R(n) x L(2) and the favorable eigenvalue behavior of the piecewise linear approximations.
Singular linear quadratic control problem for systems with linear and constant delay
NASA Astrophysics Data System (ADS)
Sesekin, A. N.; Andreeva, I. Yu.; Shlyakhov, A. S.
2016-12-01
This article is devoted to the singular linear-quadratic optimization problem on the trajectories of the linear non-autonomous system of differential equations with linear and constant delay. It should be noted that such task does not solve the class of integrable controls, so to ensure the existence of a solution is needed to expand the class of controls to include the control impulse components. For the problem under consideration, we have built program control containing impulse components in the initial and final moments time. This is done under certain assumptions on the functional and the right side of the control system.
Neural network models for Linear Programming
Culioli, J.C.; Protopopescu, V.; Britton, C.; Ericson, N. )
1989-01-01
The purpose of this paper is to present a neural network that solves the general Linear Programming (LP) problem. In the first part, we recall Hopfield and Tank's circuit for LP and show that although it converges to stable states, it does not, in general, yield admissible solutions. This is due to the penalization treatment of the constraints. In the second part, we propose an approach based on Lagragrange multipliers that converges to primal and dual admissible solutions. We also show that the duality gap (measuring the optimality) can be rendered, in principle, as small as needed. 11 refs.
Computer Program For Linear Algebra
NASA Technical Reports Server (NTRS)
Krogh, F. T.; Hanson, R. J.
1987-01-01
Collection of routines provided for basic vector operations. Basic Linear Algebra Subprogram (BLAS) library is collection from FORTRAN-callable routines for employing standard techniques to perform basic operations of numerical linear algebra.
Computer Program For Linear Algebra
NASA Technical Reports Server (NTRS)
Krogh, F. T.; Hanson, R. J.
1987-01-01
Collection of routines provided for basic vector operations. Basic Linear Algebra Subprogram (BLAS) library is collection from FORTRAN-callable routines for employing standard techniques to perform basic operations of numerical linear algebra.
Investigating Integer Restrictions in Linear Programming
ERIC Educational Resources Information Center
Edwards, Thomas G.; Chelst, Kenneth R.; Principato, Angela M.; Wilhelm, Thad L.
2015-01-01
Linear programming (LP) is an application of graphing linear systems that appears in many Algebra 2 textbooks. Although not explicitly mentioned in the Common Core State Standards for Mathematics, linear programming blends seamlessly into modeling with mathematics, the fourth Standard for Mathematical Practice (CCSSI 2010, p. 7). In solving a…
Investigating Integer Restrictions in Linear Programming
ERIC Educational Resources Information Center
Edwards, Thomas G.; Chelst, Kenneth R.; Principato, Angela M.; Wilhelm, Thad L.
2015-01-01
Linear programming (LP) is an application of graphing linear systems that appears in many Algebra 2 textbooks. Although not explicitly mentioned in the Common Core State Standards for Mathematics, linear programming blends seamlessly into modeling with mathematics, the fourth Standard for Mathematical Practice (CCSSI 2010, p. 7). In solving a…
Evaluating forest management policies by parametric linear programing
Daniel I. Navon; Richard J. McConnen
1967-01-01
An analytical and simulation technique, parametric linear programing explores alternative conditions and devises an optimal management plan for each condition. Its application in solving policy-decision problems in the management of forest lands is illustrated in an example.
Fahmida, Umi; Kolopaking, Risatianti; Santika, Otte; Sriani, Sriani; Umar, Jahja; Htet, Min Kyaw; Ferguson, Elaine
2015-03-01
Complementary feeding recommendations (CFRs) with the use of locally available foods can be developed by using linear programming (LP). Although its potential has been shown for planning phases of food-based interventions, the effectiveness in the community setting has not been tested to our knowledge. We aimed to assess effectiveness of promoting optimized CFRs for improving maternal knowledge, feeding practices, and child intakes of key problem nutrients (calcium, iron, niacin, and zinc). A community-intervention trial with a quasi-experimental design was conducted in East Lombok, West Nusa Tenggara Province, Indonesia, on children aged 9-16 mo at baseline. A CFR group (n = 240) was compared with a non-CFR group (n = 215). The CFRs, which were developed using LP, were promoted in an intervention that included monthly cooking sessions and weekly home visits. The mother's nutrition knowledge and her child's feeding practices and the child's nutrient intakes were measured before and after the 6-mo intervention by using a structured interview, 24-h recall, and 1-wk food-frequency questionnaire. The CFR intervention improved mothers' knowledge and children's feeding practices and improved children's intakes of calcium, iron, and zinc. At the end line, median (IQR) nutrient densities were significantly higher in the CFR group than in the non-CFR group for iron [i.e., 0.6 mg/100 kcal (0.4-0.8 mg/100 kcal) compared with 0.5 mg/100 kcal (0.4-0.7 mg/100 kcal)] and niacin [i.e., 0.8 mg/100 kcal (0.5-1.0 mg/100 kcal) compared with 0.6 mg/100 kcal (0.4-0.8 mg/100 kcal)]. However, median nutrient densities for calcium, iron, niacin, and zinc in the CFR group (23, 0.6, 0.7, and 0.5 mg/100 kcal, respectively) were still below desired densities (63, 1.0, 0.9, and 0.6 mg/100 kcal, respectively). The CFRs significantly increased intakes of calcium, iron, niacin, and zinc, but nutrient densities were still below desired nutrient densities. When the adoption of optimized CFRs is
Numerical stability in problems of linear algebra.
NASA Technical Reports Server (NTRS)
Babuska, I.
1972-01-01
Mathematical problems are introduced as mappings from the space of input data to that of the desired output information. Then a numerical process is defined as a prescribed recurrence of elementary operations creating the mapping of the underlying mathematical problem. The ratio of the error committed by executing the operations of the numerical process (the roundoff errors) to the error introduced by perturbations of the input data (initial error) gives rise to the concept of lambda-stability. As examples, several processes are analyzed from this point of view, including, especially, old and new processes for solving systems of linear algebraic equations with tridiagonal matrices. In particular, it is shown how such a priori information can be utilized as, for instance, a knowledge of the row sums of the matrix. Information of this type is frequently available where the system arises in connection with the numerical solution of differential equations.
Numerical stability in problems of linear algebra.
NASA Technical Reports Server (NTRS)
Babuska, I.
1972-01-01
Mathematical problems are introduced as mappings from the space of input data to that of the desired output information. Then a numerical process is defined as a prescribed recurrence of elementary operations creating the mapping of the underlying mathematical problem. The ratio of the error committed by executing the operations of the numerical process (the roundoff errors) to the error introduced by perturbations of the input data (initial error) gives rise to the concept of lambda-stability. As examples, several processes are analyzed from this point of view, including, especially, old and new processes for solving systems of linear algebraic equations with tridiagonal matrices. In particular, it is shown how such a priori information can be utilized as, for instance, a knowledge of the row sums of the matrix. Information of this type is frequently available where the system arises in connection with the numerical solution of differential equations.
Strengthening Programs through Problem Solving.
ERIC Educational Resources Information Center
Dyer, Jim
1993-01-01
Describes a secondary agricultural education program that was a dumping ground for academically disadvantaged students. Discusses how such a program can be improved by identifying problems and symptoms, treating problems, and goal setting. (JOW)
Strengthening Programs through Problem Solving.
ERIC Educational Resources Information Center
Dyer, Jim
1993-01-01
Describes a secondary agricultural education program that was a dumping ground for academically disadvantaged students. Discusses how such a program can be improved by identifying problems and symptoms, treating problems, and goal setting. (JOW)
Comparison of open-source linear programming solvers.
Gearhart, Jared Lee; Adair, Kristin Lynn; Durfee, Justin David.; Jones, Katherine A.; Martin, Nathaniel; Detry, Richard Joseph
2013-10-01
When developing linear programming models, issues such as budget limitations, customer requirements, or licensing may preclude the use of commercial linear programming solvers. In such cases, one option is to use an open-source linear programming solver. A survey of linear programming tools was conducted to identify potential open-source solvers. From this survey, four open-source solvers were tested using a collection of linear programming test problems and the results were compared to IBM ILOG CPLEX Optimizer (CPLEX) [1], an industry standard. The solvers considered were: COIN-OR Linear Programming (CLP) [2], [3], GNU Linear Programming Kit (GLPK) [4], lp_solve [5] and Modular In-core Nonlinear Optimization System (MINOS) [6]. As no open-source solver outperforms CPLEX, this study demonstrates the power of commercial linear programming software. CLP was found to be the top performing open-source solver considered in terms of capability and speed. GLPK also performed well but cannot match the speed of CLP or CPLEX. lp_solve and MINOS were considerably slower and encountered issues when solving several test problems.
Lincoln Near-Earth Asteroid Program (LINEAR)
NASA Astrophysics Data System (ADS)
Stokes, Grant H.; Evans, Jenifer B.; Viggh, Herbert E. M.; Shelly, Frank C.; Pearce, Eric C.
2000-11-01
The Lincoln Near-Earth Asteroid Research (LINEAR) program has applied electro-optical technology developed for Air Force Space Surveillance applications to the problem of discovering near-Earth asteroids (NEAs) and comets. This application is natural due to the commonality between the surveillance of the sky for man-made satellites and the search for near-Earth objects (NEOs). Both require the efficient search of broad swaths of sky to detect faint, moving objects. Currently, the Air Force Ground-based Electro-Optic Deep Space Surveillance (GEODSS) systems, which operate as part of the worldwide U.S. space surveillance network, are being upgraded to state-of-the-art charge-coupled device (CCD) detectors. These detectors are based on recent advances made by MIT Lincoln Laboratory in the fabrication of large format, highly sensitive CCDs. In addition, state-of-the-art data processing algorithms have been developed to employ the new detectors for search operations. In order to address stressing space surveillance requirements, the Lincoln CCDs have a unique combination of features, including large format, high quantum efficiency, frame transfer, high readout rate, and low noise, not found on any commercially available CCD. Systems development for the GEODSS upgrades has been accomplished at the Lincoln Laboratory Experimental Test Site (ETS) located near Socorro, New Mexico, over the past several years. Starting in 1996, the Air Force funded a small effort to demonstrate the effectiveness of the CCD and broad area search technology when applied to the problem of finding asteroids and comets. This program evolved into the current LINEAR program, which is jointly funded by the Air Force Office of Scientific Research and NASA. LINEAR, which started full operations in March of 1998, has discovered through September of 1999, 257 NEAs (of 797 known to date), 11 unusual objects (of 44 known), and 32 comets. Currently, LINEAR is contributing ∼70% of the worldwide NEA
Timetabling an Academic Department with Linear Programming.
ERIC Educational Resources Information Center
Bezeau, Lawrence M.
This paper describes an approach to faculty timetabling and course scheduling that uses computerized linear programming. After reviewing the literature on linear programming, the paper discusses the process whereby a timetable was created for a department at the University of New Brunswick. Faculty were surveyed with respect to course offerings…
Solution Methods for Stochastic Dynamic Linear Programs.
1980-12-01
Linear Programming, IIASA , Laxenburg, Austria, June 2-6, 1980. [2] Aghili, P., R.H., Cramer and H.W. Thompson, "On the applicability of two- stage...Laxenburg, Austria, May, 1978. [52] Propoi, A. and V. Krivonozhko, ’The simplex method for dynamic linear programs", RR-78-14, IIASA , Vienna, Austria
Robust Control Design via Linear Programming
NASA Technical Reports Server (NTRS)
Keel, L. H.; Bhattacharyya, S. P.
1998-01-01
This paper deals with the problem of synthesizing or designing a feedback controller of fixed dynamic order. The closed loop specifications considered here are given in terms of a target performance vector representing a desired set of closed loop transfer functions connecting various signals. In general these point targets are unattainable with a fixed order controller. By enlarging the target from a fixed point set to an interval set the solvability conditions with a fixed order controller are relaxed and a solution is more easily enabled. Results from the parametric robust control literature can be used to design the interval target family so that the performance deterioration is acceptable, even when plant uncertainty is present. It is shown that it is possible to devise a computationally simple linear programming approach that attempts to meet the desired closed loop specifications.
Convergence of linear programming using a Hopfield net
Lu, Shin-yee; Berryman, J.G.
1990-11-01
Hopfield nets are interconnected networks of simple analog Processors. Such networks have been applied to a variety of optimization problems including linear programming problems. We revised the energy function used in a Hopfield net such that the network can be implemented on a digital computer to solve linearing programming problems. We also proved that the revised discrete Hopfield net coverages, and gave the conditions of convergence. The approach is tested on two large and sparse linear programming problems. In both cases we could not reach the optimal solutions, but solutions with 1% error can be attained in less than 3 minutes of CPU time on a SUN SPARC station. The optimal solutions can be obtained by the simplex method, but required five times more CPU time. 10 refs., 1 tab.
Problem Solving and Beginning Programming.
ERIC Educational Resources Information Center
McAllister, Alan
Based on current models of problem solving within cognitive psychology, this study focused on the spontaneous problem solving strategies used by children as they first learned LOGO computer programming, and on strategy transformations that took place during the problem solving process. The research consisted of a six weeks programming training…
The Use of Linear Programming for Prediction.
ERIC Educational Resources Information Center
Schnittjer, Carl J.
The purpose of the study was to develop a linear programming model to be used for prediction, test the accuracy of the predictions, and compare the accuracy with that produced by curvilinear multiple regression analysis. (Author)
Breadboard linear array scan imager program
NASA Technical Reports Server (NTRS)
1975-01-01
The performance was evaluated of large scale integration photodiode arrays in a linear array scan imaging system breadboard for application to multispectral remote sensing of the earth's resources. Objectives, approach, implementation, and test results of the program are presented.
From Parity and Payoff Games to Linear Programming
NASA Astrophysics Data System (ADS)
Schewe, Sven
This paper establishes a surprising reduction from parity and mean payoff games to linear programming problems. While such a connection is trivial for solitary games, it is surprising for two player games, because the players have opposing objectives, whose natural translations into an optimisation problem are minimisation and maximisation, respectively. Our reduction to linear programming circumvents the need for concurrent minimisation and maximisation by replacing one of them, the maximisation, by approximation. The resulting optimisation problem can be translated to a linear programme by a simple space transformation, which is inexpensive in the unit cost model, but results in an exponential growth of the coefficients. The discovered connection opens up unexpected applications - like μ-calculus model checking - of linear programming in the unit cost model, and thus turns the intriguing academic problem of finding a polynomial time algorithm for linear programming in this model of computation (and subsequently a strongly polynomial algorithm) into a problem of paramount practical importance: All advancements in this area can immediately be applied to accelerate solving parity and payoff games, or to improve their complexity analysis.
Linear programming models for cost reimbursement.
Diehr, G; Tamura, H
1989-01-01
Tamura, Lauer, and Sanborn (1985) reported a multiple regression approach to the problem of determining a cost reimbursement (rate-setting) formula for facilities providing long-term care (nursing homes). In this article we propose an alternative approach to this problem, using an absolute-error criterion instead of the least-squares criterion used in regression, with a variety of side constraints incorporated in the derivation of the formula. The mathematical tool for implementation of this approach is linear programming (LP). The article begins with a discussion of the desirable characteristics of a rate-setting formula. The development of a formula with these properties can be easily achieved, in terms of modeling as well as computation, using LP. Specifically, LP provides an efficient computational algorithm to minimize absolute error deviation, thus protecting rates from the effects of unusual observations in the data base. LP also offers modeling flexibility to impose a variety of policy controls. These features are not readily available if a least-squares criterion is used. Examples based on actual data are used to illustrate alternative LP models for rate setting. PMID:2759871
The Future Problem Solving Program.
ERIC Educational Resources Information Center
Crabbe, Anne B.
1989-01-01
Describes the Future Problem Solving Program, in which students from the U.S. and around the world are tackling some complex challenges facing society, ranging from acid rain to terrorism. The program uses a creative problem solving process developed for business and industry. A sixth-grade toxic waste cleanup project illustrates the process.…
Deciding Tuition Structure with Linear Programming.
ERIC Educational Resources Information Center
Troutt, Marvin D.
1983-01-01
A linear programing approach is applied to college cost information to suggest optimal tuition increases under some broad policy constraints concerning consistency of the rates. Factors such as balance of credit hour and per-student charges, and differentiation by program and other student groupings, are considered. (MSE)
Extensions to the Multilevel Programming Problem
1988-05-01
OVERVIEW 2 CHAPTER 2 LITERATURE SEARCH 4 2.1 INTRODUCTION 4 2.2 RELEVANCE OF THE MODEL 6 2.3 PROBLEM FORMULATION 7 2.4 THE LINEAR BLPP 13 2.5 THE LINEAR...4.2 THE PARAMETRIC FORMULATION OF THE 0-1 BLPP 27 4.3 THE ALGORITHM 30 4.4 EXAMPLES 37 4.5 COMPUTATIONAL EXPERIENCE 43 CHAPTER 5 A BRANCH AND BOUND...ALGORITHM FOR THE BILEVEL PROGRAMMING PROBLEM 48 5.1 DEVELOPMENT OF THE KUHN-TUCKER APPROACH 48 5.2 THE ALGORITHM 52 5.3 OTHER FORMS OF THE BLPP 58 5.4
On the linearization problem for ultraspherical polynomials
NASA Astrophysics Data System (ADS)
Bassetti, B.; Montaldi, E.; Raciti, M.
1986-03-01
A direct proof of a formula established by Bressoud in 1981 [D. M. Bressoud, SIAM J. Math. Anal. 12, 161 (1981)], equivalent to the linearization formula for the ultraspherical polynomials, is given. Some related results are briefly discussed.
Positional and impulse strategies for linear problems of motion correction
NASA Astrophysics Data System (ADS)
Ananyev, B. I.; Gredasova, N. V.
2016-12-01
Control problems for a linear system with incomplete information are considered. It is supposed that a linear signal with an additive noise is observed. This noise along with the disturbances in the state equation is bounded by the quadratic constraints. The control action in the state equation may be contained in a compact set. In the second case, the total variation of the control is restricted. This case leads us to a sequence of impulse control actions (delta-functions). For both cases, we obtain the definite relations for optimal control actions that guarantee the minimax value of the terminal functional. We use methods of the control theory under uncertainty and the dynamic programming. Some examples from the theory of the movement of space and flight vehicles are investigated.
A multistage linear array assignment problem
NASA Technical Reports Server (NTRS)
Nicol, David M.; Shier, D. R.; Kincaid, R. K.; Richards, D. S.
1988-01-01
The implementation of certain algorithms on parallel processing computing architectures can involve partitioning contiguous elements into a fixed number of groups, each of which is to be handled by a single processor. It is desired to find an assignment of elements to processors that minimizes the sum of the maximum workloads experienced at each stage. This problem can be viewed as a multi-objective network optimization problem. Polynomially-bounded algorithms are developed for the case of two stages, whereas the associated decision problem (for an arbitrary number of stages) is shown to be NP-complete. Heuristic procedures are therefore proposed and analyzed for the general problem. Computational experience with one of the exact problems, incorporating certain pruning rules, is presented with one of the exact problems. Empirical results also demonstrate that one of the heuristic procedures is especially effective in practice.
Fuzzy linear programming for bulb production
NASA Astrophysics Data System (ADS)
Siregar, I.; Suantio, H.; Hanifiah, Y.; Muchtar, M. A.; Nasution, T. H.
2017-01-01
The research was conducted at a bulb company. This company has a high market demand. The increasing of the market demand has caused the company’s production could not fulfill the demand due to production planning is not optimal. Bulb production planning is researched with the aim to enable the company to fulfill the market demand in accordance with the limited resources available. From the data, it is known that the company cannot reach the market demand in the production of the Type A and Type B bulb. In other hands, the Type C bulb is produced exceeds market demand. By using fuzzy linear programming, then obtained the optimal production plans and to reach market demand. Completion of the simple method is done by using software LINGO 13. Application of fuzzy linear programming is being able to increase profits amounted to 7.39% of the ordinary concept of linear programming.
Stochastic Optimal Control and Linear Programming Approach
Buckdahn, R.; Goreac, D.; Quincampoix, M.
2011-04-15
We study a classical stochastic optimal control problem with constraints and discounted payoff in an infinite horizon setting. The main result of the present paper lies in the fact that this optimal control problem is shown to have the same value as a linear optimization problem stated on some appropriate space of probability measures. This enables one to derive a dual formulation that appears to be strongly connected to the notion of (viscosity sub) solution to a suitable Hamilton-Jacobi-Bellman equation. We also discuss relation with long-time average problems.
Primal-Dual Methods for Linear Programming
1991-05-01
Dulce B. Poncele6n and Michael A. Saunders TECHNICAL REPORT SOL 91-3 May 1991 Department of Operations-Research Stanford University 91-03882Stanford, CA...for Linear Programming by Philip E. Gill, Walter Murray, Dulce B. Poncele6n and Michael A. Saunders TECHNICAL REPORT SOL 91-3 May 1991 U ’ .mve dj 1...DUAL METHODS FOR LINEAR PROGRAMMING* Philip E. GILLt Walter MURRAY$ Dulce B. PONCELE6N§ and Michael A. SAUNDERS t Technical Report SOL 91-31 May 1991
A Partitioning and Bounded Variable Algorithm for Linear Programming
ERIC Educational Resources Information Center
Sheskin, Theodore J.
2006-01-01
An interesting new partitioning and bounded variable algorithm (PBVA) is proposed for solving linear programming problems. The PBVA is a variant of the simplex algorithm which uses a modified form of the simplex method followed by the dual simplex method for bounded variables. In contrast to the two-phase method and the big M method, the PBVA does…
On the Feasibility of a Generalized Linear Program
1989-03-01
generealized linear program by applying the same algorithm to a "phase-one" problem without requiring that the initial basic feasible solution to the latter be non-degenerate. secUrMTY C.AMlIS CAYI S OP ?- PAeES( UII -W & ,
A Partitioning and Bounded Variable Algorithm for Linear Programming
ERIC Educational Resources Information Center
Sheskin, Theodore J.
2006-01-01
An interesting new partitioning and bounded variable algorithm (PBVA) is proposed for solving linear programming problems. The PBVA is a variant of the simplex algorithm which uses a modified form of the simplex method followed by the dual simplex method for bounded variables. In contrast to the two-phase method and the big M method, the PBVA does…
Optimized remedial groundwater extraction using linear programming
Quinn, J.J.
1995-12-31
Groundwater extraction systems are typically installed to remediate contaminant plumes or prevent further spread of contamination. These systems are expensive to install and maintain. A traditional approach to designing such a wellfield uses a series of trial-and-error simulations to test the effects of various well locations and pump rates. However, the optimal locations and pump rates of extraction wells are difficult to determine when objectives related to the site hydrogeology and potential pumping scheme are considered. This paper describes a case study of an application of linear programming theory to determine optimal well placement and pump rates. The objectives of the pumping scheme were to contain contaminant migration and reduce contaminant concentrations while minimizing the total amount of water pumped and treated. Past site activities at the area under study included disposal of contaminants in pits. Several groundwater plumes have been identified, and others may be present. The area of concern is bordered on three sides by a wetland, which receives a portion of its input budget as groundwater discharge from the pits. Optimization of the containment pumping scheme was intended to meet three goals: (1) prevent discharge of contaminated groundwater to the wetland, (2) minimize the total water pumped and treated (cost benefit), and (3) avoid dewatering of the wetland (cost and ecological benefits). Possible well locations were placed at known source areas. To constrain the problem, the optimization program was instructed to prevent any flow toward the wetland along a user-specified border. In this manner, the optimization routine selects well locations and pump rates so that a groundwater divide is produced along this boundary.
Planning under uncertainty solving large-scale stochastic linear programs
Infanger, G. |
1992-12-01
For many practical problems, solutions obtained from deterministic models are unsatisfactory because they fail to hedge against certain contingencies that may occur in the future. Stochastic models address this shortcoming, but up to recently seemed to be intractable due to their size. Recent advances both in solution algorithms and in computer technology now allow us to solve important and general classes of practical stochastic problems. We show how large-scale stochastic linear programs can be efficiently solved by combining classical decomposition and Monte Carlo (importance) sampling techniques. We discuss the methodology for solving two-stage stochastic linear programs with recourse, present numerical results of large problems with numerous stochastic parameters, show how to efficiently implement the methodology on a parallel multi-computer and derive the theory for solving a general class of multi-stage problems with dependency of the stochastic parameters within a stage and between different stages.
Linear inverse problem of the reactor dynamics
NASA Astrophysics Data System (ADS)
Volkov, N. P.
2017-01-01
The aim of this work is the study transient processes in nuclear reactors. The mathematical model of the reactor dynamics excluding reverse thermal coupling is investigated. This model is described by a system of integral-differential equations, consisting of a non-stationary anisotropic multispeed kinetic transport equation and a delayed neutron balance equation. An inverse problem was formulated to determine the stationary part of the function source along with the solution of the direct problem. The author obtained sufficient conditions for the existence and uniqueness of a generalized solution of this inverse problem.
AN INTRODUCTION TO THE APPLICATION OF DYNAMIC PROGRAMMING TO LINEAR CONTROL SYSTEMS
DYNAMIC PROGRAMMING APPLIED TO OPTIMIZE LINEAR CONTROL SYSTEMS WITH QUADRATIC PERFORMANCE MEASURES. MATHEMATICAL METHODS WHICH MAY BE APPLIED TO SPACE VEHICLE AND RELATED GUIDANCE AND CONTROL PROBLEMS.
Spline smoothing of histograms by linear programming
NASA Technical Reports Server (NTRS)
Bennett, J. O.
1972-01-01
An algorithm for an approximating function to the frequency distribution is obtained from a sample of size n. To obtain the approximating function a histogram is made from the data. Next, Euclidean space approximations to the graph of the histogram using central B-splines as basis elements are obtained by linear programming. The approximating function has area one and is nonnegative.
Inverting feedforward neural networks using linear and nonlinear programming.
Lu, B L; Kita, H; Nishikawa, Y
1999-01-01
The problem of inverting trained feedforward neural networks is to find the inputs which yield a given output. In general, this problem is an ill-posed problem because the mapping from the output space to the input space is a one-to-many mapping. In this paper, we present a method for dealing with the inverse problem by using mathematical programming techniques. The principal idea behind the method is to formulate the inverse problem as a nonlinear programming (NLP) problem, a separable programming (SP) problem, or a linear programming (LP) problem according to the architectures of networks to be inverted or the types of network inversions to be computed. An important advantage of the method over the existing iterative inversion algorithm is that various designated network inversions of multilayer perceptrons (MLP's) and radial basis function (RBF) neural networks can be obtained by solving the corresponding SP problems, which can be solved by a modified simplex method, a well-developed and efficient method for solving LP problems. We present several examples to demonstrate the proposed method and the applications of network inversions to examining and improving the generalization performance of trained networks. The results show the effectiveness of the proposed method.
Synthesizing Dynamic Programming Algorithms from Linear Temporal Logic Formulae
NASA Technical Reports Server (NTRS)
Rosu, Grigore; Havelund, Klaus
2001-01-01
The problem of testing a linear temporal logic (LTL) formula on a finite execution trace of events, generated by an executing program, occurs naturally in runtime analysis of software. We present an algorithm which takes an LTL formula and generates an efficient dynamic programming algorithm. The generated algorithm tests whether the LTL formula is satisfied by a finite trace of events given as input. The generated algorithm runs in linear time, its constant depending on the size of the LTL formula. The memory needed is constant, also depending on the size of the formula.
The stability problem for linear multistep methods
NASA Astrophysics Data System (ADS)
Aceto, L.; Trigiante, D.
2007-12-01
The paper reviews results on rigorous proofs for stability properties of classes of linear multistep methods (LMMs) used either as IVMs or as BVMs. The considered classes are not only the well-known classical ones (BDF, Adams, ...) along with their BVM correspondent, but also those which were considered unstable as IVMs, but stable as BVMs. Among the latter we find two classes which deserve attention because of their peculiarity: the TOMs (top order methods) which have the highest order allowed to a LMM and the Bs-LMMs which have the property to carry with each method its natural continuous extension.
Train repathing in emergencies based on fuzzy linear programming.
Meng, Xuelei; Cui, Bingmou
2014-01-01
Train pathing is a typical problem which is to assign the train trips on the sets of rail segments, such as rail tracks and links. This paper focuses on the train pathing problem, determining the paths of the train trips in emergencies. We analyze the influencing factors of train pathing, such as transferring cost, running cost, and social adverse effect cost. With the overall consideration of the segment and station capability constraints, we build the fuzzy linear programming model to solve the train pathing problem. We design the fuzzy membership function to describe the fuzzy coefficients. Furthermore, the contraction-expansion factors are introduced to contract or expand the value ranges of the fuzzy coefficients, coping with the uncertainty of the value range of the fuzzy coefficients. We propose a method based on triangular fuzzy coefficient and transfer the train pathing (fuzzy linear programming model) to a determinate linear model to solve the fuzzy linear programming problem. An emergency is supposed based on the real data of the Beijing-Shanghai Railway. The model in this paper was solved and the computation results prove the availability of the model and efficiency of the algorithm.
Train Repathing in Emergencies Based on Fuzzy Linear Programming
Cui, Bingmou
2014-01-01
Train pathing is a typical problem which is to assign the train trips on the sets of rail segments, such as rail tracks and links. This paper focuses on the train pathing problem, determining the paths of the train trips in emergencies. We analyze the influencing factors of train pathing, such as transferring cost, running cost, and social adverse effect cost. With the overall consideration of the segment and station capability constraints, we build the fuzzy linear programming model to solve the train pathing problem. We design the fuzzy membership function to describe the fuzzy coefficients. Furthermore, the contraction-expansion factors are introduced to contract or expand the value ranges of the fuzzy coefficients, coping with the uncertainty of the value range of the fuzzy coefficients. We propose a method based on triangular fuzzy coefficient and transfer the train pathing (fuzzy linear programming model) to a determinate linear model to solve the fuzzy linear programming problem. An emergency is supposed based on the real data of the Beijing-Shanghai Railway. The model in this paper was solved and the computation results prove the availability of the model and efficiency of the algorithm. PMID:25121128
A piecewise linear approximation scheme for hereditary optimal control problems
NASA Technical Reports Server (NTRS)
Cliff, E. M.; Burns, J. A.
1977-01-01
An approximation scheme based on 'piecewise linear' approximations of L2 spaces is employed to formulate a numerical method for solving quadratic optimal control problems governed by linear retarded functional differential equations. This piecewise linear method is an extension of the so called averaging technique. It is shown that the Riccati equation for the linear approximation is solved by simple transformation of the averaging solution. Thus, the computational requirements are essentially the same. Numerical results are given.
A piecewise linear approximation scheme for hereditary optimal control problems
NASA Technical Reports Server (NTRS)
Cliff, E. M.; Burns, J. A.
1977-01-01
An approximation scheme based on 'piecewise linear' approximations of L2 spaces is employed to formulate a numerical method for solving quadratic optimal control problems governed by linear retarded functional differential equations. This piecewise linear method is an extension of the so called averaging technique. It is shown that the Riccati equation for the linear approximation is solved by simple transformation of the averaging solution. Thus, the computational requirements are essentially the same. Numerical results are given.
Controller design approach based on linear programming.
Tanaka, Ryo; Shibasaki, Hiroki; Ogawa, Hiromitsu; Murakami, Takahiro; Ishida, Yoshihisa
2013-11-01
This study explains and demonstrates the design method for a control system with a load disturbance observer. Observer gains are determined by linear programming (LP) in terms of the Routh-Hurwitz stability criterion and the final-value theorem. In addition, the control model has a feedback structure, and feedback gains are determined to be the linear quadratic regulator. The simulation results confirmed that compared with the conventional method, the output estimated by our proposed method converges to a reference input faster when a load disturbance is added to a control system. In addition, we also confirmed the effectiveness of the proposed method by performing an experiment with a DC motor.
A LINEAR PROGRAMMING MODEL OF THE GASEOUSDIFFUSION ISOTOPE-SEPARATION PROCESS,
ISOTOPE SEPARATION, LINEAR PROGRAMMING ), (*GASEOUS DIFFUSION SEPARATION, LINEAR PROGRAMMING ), (* LINEAR PROGRAMMING , GASEOUS DIFFUSION SEPARATION), NUCLEAR REACTORS, REACTOR FUELS, URANIUM, PURIFICATION
Breathing Problems: An Individualized Program.
ERIC Educational Resources Information Center
Vodola, Thomas M.
As one of the components of the Project ACTIVE (All Children Totally Involved Exercising) Teacher Training Model Kit, the manual is designed to enable the educator to organize, conduct, and evaluate individualized-personalized physical education programs for children (prekindergarten through high school) with breathing problems. An introductory…
Boundary control problem of linear Stokes equation with point observations
Ding, Z.
1994-12-31
We will discuss the linear quadratic regulator problems (LQR) of linear Stokes system with point observations on the boundary and box constraints on the boundary control. By using hydropotential theory, we proved that the LQR problems without box constraint on the control do not admit any non trivial solution, while the LQR problems with box constraints have a unique solution. The optimal control is given explicitly, and its singular behaviors are displayed explicitly through a decomposition formula. Based upon the characteristic formula of the optimal control, a generic numerical algorithm is given for solving the box constrained LQR problems.
Multisplitting for linear, least squares and nonlinear problems
Renaut, R.
1996-12-31
In earlier work, presented at the 1994 Iterative Methods meeting, a multisplitting (MS) method of block relaxation type was utilized for the solution of the least squares problem, and nonlinear unconstrained problems. This talk will focus on recent developments of the general approach and represents joint work both with Andreas Frommer, University of Wupertal for the linear problems and with Hans Mittelmann, Arizona State University for the nonlinear problems.
Experiences with linear solvers for oil reservoir simulation problems
Joubert, W.; Janardhan, R.; Biswas, D.; Carey, G.
1996-12-31
This talk will focus on practical experiences with iterative linear solver algorithms used in conjunction with Amoco Production Company`s Falcon oil reservoir simulation code. The goal of this study is to determine the best linear solver algorithms for these types of problems. The results of numerical experiments will be presented.
Linear programming using symmetric triangular intuitionistic fuzzy numbers
NASA Astrophysics Data System (ADS)
Parvathi, R.; Malathi, C.
2012-09-01
This paper introduces Symmetric Triangular Intuitionistic Fuzzy Numbers (STriFNs) and also proposes a new type of intuitionistic fuzzy arithmetic operations on STriIFNs. A special ranking function for ordering STriIFNs has been introduced. A solution methodology for Intuitionistic Fuzzy Linear Programming Problems (IFLPPs) with STriIFNs as parameters has been proposed by using Intuitionistic Fuzzy Simplex Method and the arithmetic operations on STriIFNs. Finally, an illustrative numerical example is presented to demonstrate the proposed approach.
Linear Programming Problems for Generalized Uncertainty
ERIC Educational Resources Information Center
Thipwiwatpotjana, Phantipa
2010-01-01
Uncertainty occurs when there is more than one realization that can represent an information. This dissertation concerns merely discrete realizations of an uncertainty. Different interpretations of an uncertainty and their relationships are addressed when the uncertainty is not a probability of each realization. A well known model that can handle…
Linear Programming Problems for Generalized Uncertainty
ERIC Educational Resources Information Center
Thipwiwatpotjana, Phantipa
2010-01-01
Uncertainty occurs when there is more than one realization that can represent an information. This dissertation concerns merely discrete realizations of an uncertainty. Different interpretations of an uncertainty and their relationships are addressed when the uncertainty is not a probability of each realization. A well known model that can handle…
The synthesis of optimal controls for linear, time-optimal problems with retarded controls.
NASA Technical Reports Server (NTRS)
Banks, H. T.; Jacobs, M. Q.; Latina, M. R.
1971-01-01
Optimization problems involving linear systems with retardations in the controls are studied in a systematic way. Some physical motivation for the problems is discussed. The topics covered are: controllability, existence and uniqueness of the optimal control, sufficient conditions, techniques of synthesis, and dynamic programming. A number of solved examples are presented.
Inverse Modelling Problems in Linear Algebra Undergraduate Courses
ERIC Educational Resources Information Center
Martinez-Luaces, Victor E.
2013-01-01
This paper will offer an analysis from a theoretical point of view of mathematical modelling, applications and inverse problems of both causation and specification types. Inverse modelling problems give the opportunity to establish connections between theory and practice and to show this fact, a simple linear algebra example in two different…
Inverse Modelling Problems in Linear Algebra Undergraduate Courses
ERIC Educational Resources Information Center
Martinez-Luaces, Victor E.
2013-01-01
This paper will offer an analysis from a theoretical point of view of mathematical modelling, applications and inverse problems of both causation and specification types. Inverse modelling problems give the opportunity to establish connections between theory and practice and to show this fact, a simple linear algebra example in two different…
On the Displacement Problem of Plane Linear Elastostatics
NASA Astrophysics Data System (ADS)
Russo, R.
2010-09-01
We consider the displacement problem of linear elastostatics in a Lipschitz exterior domain of R2. We prove that if the boundary datum a lies in L2(∂Ω), then the problem has a unique very weak solution which converges to an assigned constant vector u∞ at infinity if and if a and u∞ satisfy a suitable compatibility condition.
Fuzzy Linear Programming and its Application in Home Textile Firm
NASA Astrophysics Data System (ADS)
Vasant, P.; Ganesan, T.; Elamvazuthi, I.
2011-06-01
In this paper, new fuzzy linear programming (FLP) based methodology using a specific membership function, named as modified logistic membership function is proposed. The modified logistic membership function is first formulated and its flexibility in taking up vagueness in parameter is established by an analytical approach. The developed methodology of FLP has provided a confidence in applying to real life industrial production planning problem. This approach of solving industrial production planning problem can have feedback with the decision maker, the implementer and the analyst.
Optimized groundwater containment using linear programming
Quinn, J.J.; Johnson, R.L.; Durham, L.A.
1998-07-01
Groundwater extraction systems are typically installed to contain contaminant plumes. These systems are expensive to install and maintain. A traditional approach to designing such a wellfield is to use a series of trial-and-error simulations to test the effects of various well locations and pump rates. However, optimal locations and pump rates of extraction wells are difficult to determine when the objectives of the potential pumping scheme and the site hydrogeology are considered. This paper describes a case study of an application of linear programming theory to determine optimal well placement and pump rates. Calculations were conducted by using ModMan to link a calibrated MODFLOW flow model with LINDO, a linear programming package. Past activities at the site under study included disposal of contaminants in pits. Several groundwater plumes have been identified, and others may be present. The area of concern is bordered on three sides by a wetland, which receives a portion of its input water budget as groundwater discharge from the disposal area. The objective function of the optimization was to minimize the rate of groundwater extraction while preventing discharge to the marsh across a user-specified boundary. In this manner, the optimization routine selects well locations and pump rates to produce a groundwater divide along this boundary.
Consensus contact prediction by linear programming.
Gao, Xin; Bu, Dongbo; Li, Shuai Cheng; Li, Ming; Xu, Jinbo
2007-01-01
Protein inter-residue contacts are of great use for protein structure determination or prediction. Recent CASP events have shown that a few accurately predicted contacts can help improve both computational efficiency and prediction accuracy of the ab inito folding methods. This paper develops an integer linear programming (ILP) method for consensus-based contact prediction. In contrast to the simple "majority voting" method assuming that all the individual servers are equal and independent, our method evaluates their correlations using the maximum likelihood method and constructs some latent independent servers using the principal component analysis technique. Then, we use an integer linear programming model to assign weights to these latent servers in order to maximize the deviation between the correct contacts and incorrect ones; our consensus prediction server is the weighted combination of these latent servers. In addition to the consensus information, our method also uses server-independent correlated mutation (CM) as one of the prediction features. Experimental results demonstrate that our contact prediction server performs better than the "majority voting" method. The accuracy of our method for the top L/5 contacts on CASP7 targets is 73.41%, which is much higher than previously reported studies. On the 16 free modeling (FM) targets, our method achieves an accuracy of 37.21%.
Local regularization of linear inverse problems via variational filtering
NASA Astrophysics Data System (ADS)
Lamm, Patricia K.
2017-08-01
We develop local regularization methods for ill-posed linear inverse problems governed by general Fredholm integral operators. The methods are executed as filtering algorithms which are simple to implement and computationally efficient for a large class of problems. We establish a convergence theory and give convergence rates for such methods, and illustrate their computational speed in numerical tests for inverse problems in geomagnetic exploration and imaging.
Voila: A visual object-oriented iterative linear algebra problem solving environment
Edwards, H.C.; Hayes, L.J.
1994-12-31
Application of iterative methods to solve a large linear system of equations currently involves writing a program which calls iterative method subprograms from a large software package. These subprograms have complex interfaces which are difficult to use and even more difficult to program. A problem solving environment specifically tailored to the development and application of iterative methods is needed. This need will be fulfilled by Voila, a problem solving environment which provides a visual programming interface to object-oriented iterative linear algebra kernels. Voila will provide several quantum improvements over current iterative method problem solving environments. First, programming and applying iterative methods is considerably simplified through Voila`s visual programming interface. Second, iterative method algorithm implementations are independent of any particular sparse matrix data structure through Voila`s object-oriented kernels. Third, the compile-link-debug process is eliminated as Voila operates as an interpreter.
MAGDM linear-programming models with distinct uncertain preference structures.
Xu, Zeshui S; Chen, Jian
2008-10-01
Group decision making with preference information on alternatives is an interesting and important research topic which has been receiving more and more attention in recent years. The purpose of this paper is to investigate multiple-attribute group decision-making (MAGDM) problems with distinct uncertain preference structures. We develop some linear-programming models for dealing with the MAGDM problems, where the information about attribute weights is incomplete, and the decision makers have their preferences on alternatives. The provided preference information can be represented in the following three distinct uncertain preference structures: 1) interval utility values; 2) interval fuzzy preference relations; and 3) interval multiplicative preference relations. We first establish some linear-programming models based on decision matrix and each of the distinct uncertain preference structures and, then, develop some linear-programming models to integrate all three structures of subjective uncertain preference information provided by the decision makers and the objective information depicted in the decision matrix. Furthermore, we propose a simple and straightforward approach in ranking and selecting the given alternatives. It is worth pointing out that the developed models can also be used to deal with the situations where the three distinct uncertain preference structures are reduced to the traditional ones, i.e., utility values, fuzzy preference relations, and multiplicative preference relations. Finally, we use a practical example to illustrate in detail the calculation process of the developed approach.
A User’s Manual for Interactive Linear Control Programs on IBM/3033.
1982-12-01
There existed a need for an interactive program that would provide the user assistance it solving applications of linear control theory. The linear ...analysis, design and simulation of a broad class of linear control problems. LINCON consists of two groups: matrix manipulation, transfer function and... control program (LINCON) and its user’s guide satisfy this need. A series of ten interactive programs are presented which permit the user to carry out
Longitudinal force distribution using quadratically constrained linear programming
NASA Astrophysics Data System (ADS)
Klomp, M.
2011-12-01
In this paper, a new method is presented for the optimisation of force distribution for combined traction/braking and cornering. In order to provide a general, simple and flexible problem formulation, the optimisation is addressed as a quadratically constrained linear programming (QCLP) problem. Apart from fast numerical solutions, different driveline configurations can be included in the QCLP problem in a very straightforward fashion. The optimisation of the distribution of the individual wheel forces using the quasi-steady-state assumption is known to be useful for the study of the influence of particular driveline configurations on the combined lateral and longitudinal grip envelope of a particular vehicle-driveline configuration. The addition of the QCLP problem formulation makes another powerful tool available to the vehicle dynamics analyst to perform such studies.
Direct linear programming solver in C for structural applications
NASA Astrophysics Data System (ADS)
Damkilde, L.; Hoyer, O.; Krenk, S.
1994-08-01
An optimization problem can be characterized by an object-function, which is maximized, and restrictions, which limit the variation of the variables. A subclass of optimization is Linear Programming (LP), where both the object-function and the restrictions are linear functions of the variables. The traditional solution methods for LP problems are based on the simplex method, and it is customary to allow only non-negative variables. Compared to other optimization routines the LP solvers are more robust and the optimum is reached in a finite number of steps and is not sensitive to the starting point. For structural applications many optimization problems can be linearized and solved by LP routines. However, the structural variables are not always non-negative, and this requires a reformation, where a variable x is substituted by the difference of two non-negative variables, x(sup + ) and x(sup - ). The transformation causes a doubling of the number of variables, and in a computer implementation the memory allocation doubles and for a typical problem the execution time at least doubles. This paper describes a LP solver written in C, which can handle a combination of non-negative variables and unlimited variables. The LP solver also allows restart, and this may reduce the computational costs if the solution to a similar LP problem is known a priori. The algorithm is based on the simplex method, and differs only in the logical choices. Application of the new LP solver will at the same time give both a more direct problem formulation and a more efficient program.
The box method for linear programming: Part 1, Basic theory
Zikan, K.; Cottle, R.W.
1987-06-01
This paper presents a new interior-point algorithm for linear programming where the constraints are all expressed as inequalities. Along with the concept of ''minimum-weight basis'', the algorithm features a novel mechanism for finding search directions. Unlike other interior-point methods which implicitly or explicitly involve optimization over ellipsoids for their direction-finding schemes, the one reported here uses ''boxes''. The corresponding subproblems are simple linear programs having closed form solutions. It is shown that the iterates generated by the algorithm converge to an extreme point of the feasible region. When this point is nondegenerate, it is optimal and reached within finitely any steps. The methodology introduced here also gives rise to a polyhedral subdivision of the problem's feasible region and in fact to the entire space of decision variables.
Ensemble segmentation using efficient integer linear programming.
Alush, Amir; Goldberger, Jacob
2012-10-01
We present a method for combining several segmentations of an image into a single one that in some sense is the average segmentation in order to achieve a more reliable and accurate segmentation result. The goal is to find a point in the "space of segmentations" which is close to all the individual segmentations. We present an algorithm for segmentation averaging. The image is first oversegmented into superpixels. Next, each segmentation is projected onto the superpixel map. An instance of the EM algorithm combined with integer linear programming is applied on the set of binary merging decisions of neighboring superpixels to obtain the average segmentation. Apart from segmentation averaging, the algorithm also reports the reliability of each segmentation. The performance of the proposed algorithm is demonstrated on manually annotated images from the Berkeley segmentation data set and on the results of automatic segmentation algorithms.
LPNORM: A linear programming normative analysis code
NASA Astrophysics Data System (ADS)
de Caritat, Patrice; Bloch, John; Hutcheon, Ian
1994-04-01
The computer code LPNORM implements the mathematical method of linear programming to calculate the mineralogical makeup of mineral mixtures, such as rock, sediment, or soil samples, from their bulk geochemical composition and from the mineralogical (or geochemical) composition of the contained minerals. This method simultaneously solves the set of linear equations governing the distribution of oxides into these minerals, subject to an objective function and a set of basic constraints. LPNORM allows the user to specify what minerals will be considered for normative analysis, what their composition is (in terms of mineral formula or geochemical composition), and whether to maximize mineral abundances, minimize slack variables (oxides that can not be accounted for), or do both at once in the objective function. Independent knowledge about the abundance of one or several of the minerals in the sample can be entered as additional equality or inequality constraints. Trial-and-error approach enables the user to "optimize" the composition of one or a few of the contained minerals. Results of comparative tests, highlighting the efficiency, as well as the shortcomings, of LPNORM are presented.
Linear programming for learning in neural networks
NASA Astrophysics Data System (ADS)
Raghavan, Raghu
1991-08-01
The authors have previously proposed a network of probabilistic cellular automata (PCAs) as part of an image recognition system designed to integrate model-based and data-driven approaches in a connectionist framework. The PCA arises from some natural requirements on the system which include incorporation of prior knowledge such as in inference rules, locality of inferences, and full parallelism. This network has been applied to recognize objects in both synthetic and in real data. This approach achieves recognition through the short-, rather than the long-time behavior of the dynamics of the PCA. In this paper, some methods are developed for learning the connection strengths by solving linear inequalities: the figures of merit are tendencies or directions of movement of the dynamical system. These 'dynamical' figures of merit result in inequality constraints on the connection strengths which are solved by linear (LP) or quadratic programs (QP). An algorithm is described for processing a large number of samples to determine weights for the PCA. The work may be regarded as either pointing out another application for constrained optimization, or as pointing out the need to extend the perceptron and similar methods for learning. The extension is needed because the neural network operates on a different principle from that for which the perceptron method was devised.
Particle swarm optimization - Genetic algorithm (PSOGA) on linear transportation problem
NASA Astrophysics Data System (ADS)
Rahmalia, Dinita
2017-08-01
Linear Transportation Problem (LTP) is the case of constrained optimization where we want to minimize cost subject to the balance of the number of supply and the number of demand. The exact method such as northwest corner, vogel, russel, minimal cost have been applied at approaching optimal solution. In this paper, we use heurisitic like Particle Swarm Optimization (PSO) for solving linear transportation problem at any size of decision variable. In addition, we combine mutation operator of Genetic Algorithm (GA) at PSO to improve optimal solution. This method is called Particle Swarm Optimization - Genetic Algorithm (PSOGA). The simulations show that PSOGA can improve optimal solution resulted by PSO.
User's manual for LINEAR, a FORTRAN program to derive linear aircraft models
NASA Technical Reports Server (NTRS)
Duke, Eugene L.; Patterson, Brian P.; Antoniewicz, Robert F.
1987-01-01
This report documents a FORTRAN program that provides a powerful and flexible tool for the linearization of aircraft models. The program LINEAR numerically determines a linear system model using nonlinear equations of motion and a user-supplied nonlinear aerodynamic model. The system model determined by LINEAR consists of matrices for both state and observation equations. The program has been designed to allow easy selection and definition of the state, control, and observation variables to be used in a particular model.
Lu, Bao-Liang; Ito, Koji
2003-09-01
In this paper we present a method for converting general nonlinear programming (NLP) problems into separable programming (SP) problems by using feedforward neural networks (FNNs). The basic idea behind the method is to use two useful features of FNNs: their ability to approximate arbitrary continuous nonlinear functions with a desired degree of accuracy and their ability to express nonlinear functions in terms of parameterized compositions of functions of single variables. According to these two features, any nonseparable objective functions and/or constraints in NLP problems can be approximately expressed as separable functions with FNNs. Therefore, any NLP problems can be converted into SP problems. The proposed method has three prominent features. (a) It is more general than existing transformation techniques; (b) it can be used to formulate optimization problems as SP problems even when their precise analytic objective function and/or constraints are unknown; (c) the SP problems obtained by the proposed method may highly facilitate the selection of grid points for piecewise linear approximation of nonlinear functions. We analyze the computational complexity of the proposed method and compare it with an existing transformation approach. We also present several examples to demonstrate the method and the performance of the simplex method with the restricted basis entry rule for solving SP problems.
Unique radiation problems associated with the SLAC Linear Collider
Jenkins, T.M.; Nelson, W.R.
1987-01-01
The SLAC Linear Collider (SLC) is a variation of a new class of linear colliders whereby two linear accelerators are aimed at each other to collide intense bunches of electrons and positrons together. Conventional storage rings are becoming ever more costly as the energy of the stored beams increases such that the cost of two linear colliders per GeV is less than that of electron-positron storage rings at cm energies above about 100 GeV. The SLC being built at SLAC is designed to achieve a center-of-mass energy of 100 GeV by accelerating intense bunches of particles, both electrons and positrons, in the SLAC linac and transporting them along two different arcs to a point where they are focused to a small radius and made to collide head on. The SLC has two main goals. The first is to develop the physics and technology of linear colliders. The other is to achieve center-of-mass energies above 90 GeV in order to investigate the unification of the weak and electromagnetic interactions in the energy range above 90 GeV; (i.e., Z/sup 0/, etc.). This note discusses a few of the special problems that were encountered by the Radiation Physics group at SLAC during the design and construction of the SLAC Linear Collider. The nature of these problems is discussed along with the methods employed to solve them.
Towards lexicographic multi-objective linear programming using grossone methodology
NASA Astrophysics Data System (ADS)
Cococcioni, Marco; Pappalardo, Massimo; Sergeyev, Yaroslav D.
2016-10-01
Lexicographic Multi-Objective Linear Programming (LMOLP) problems can be solved in two ways: preemptive and nonpreemptive. The preemptive approach requires the solution of a series of LP problems, with changing constraints (each time the next objective is added, a new constraint appears). The nonpreemptive approach is based on a scalarization of the multiple objectives into a single-objective linear function by a weighted combination of the given objectives. It requires the specification of a set of weights, which is not straightforward and can be time consuming. In this work we present both mathematical and software ingredients necessary to solve LMOLP problems using a recently introduced computational methodology (allowing one to work numerically with infinities and infinitesimals) based on the concept of grossone. The ultimate goal of such an attempt is an implementation of a simplex-like algorithm, able to solve the original LMOLP problem by solving only one single-objective problem and without the need to specify finite weights. The expected advantages are therefore obvious.
Sparse stochastic processes and discretization of linear inverse problems.
Bostan, Emrah; Kamilov, Ulugbek S; Nilchian, Masih; Unser, Michael
2013-07-01
We present a novel statistically-based discretization paradigm and derive a class of maximum a posteriori (MAP) estimators for solving ill-conditioned linear inverse problems. We are guided by the theory of sparse stochastic processes, which specifies continuous-domain signals as solutions of linear stochastic differential equations. Accordingly, we show that the class of admissible priors for the discretized version of the signal is confined to the family of infinitely divisible distributions. Our estimators not only cover the well-studied methods of Tikhonov and l1-type regularizations as particular cases, but also open the door to a broader class of sparsity-promoting regularization schemes that are typically nonconvex. We provide an algorithm that handles the corresponding nonconvex problems and illustrate the use of our formalism by applying it to deconvolution, magnetic resonance imaging, and X-ray tomographic reconstruction problems. Finally, we compare the performance of estimators associated with models of increasing sparsity.
A linear programming approach for optimal contrast-tone mapping.
Wu, Xiaolin
2011-05-01
This paper proposes a novel algorithmic approach of image enhancement via optimal contrast-tone mapping. In a fundamental departure from the current practice of histogram equalization for contrast enhancement, the proposed approach maximizes expected contrast gain subject to an upper limit on tone distortion and optionally to other constraints that suppress artifacts. The underlying contrast-tone optimization problem can be solved efficiently by linear programming. This new constrained optimization approach for image enhancement is general, and the user can add and fine tune the constraints to achieve desired visual effects. Experimental results demonstrate clearly superior performance of the new approach over histogram equalization and its variants.
A scalable parallel algorithm for multiple objective linear programs
NASA Technical Reports Server (NTRS)
Wiecek, Malgorzata M.; Zhang, Hong
1994-01-01
This paper presents an ADBASE-based parallel algorithm for solving multiple objective linear programs (MOLP's). Job balance, speedup and scalability are of primary interest in evaluating efficiency of the new algorithm. Implementation results on Intel iPSC/2 and Paragon multiprocessors show that the algorithm significantly speeds up the process of solving MOLP's, which is understood as generating all or some efficient extreme points and unbounded efficient edges. The algorithm gives specially good results for large and very large problems. Motivation and justification for solving such large MOLP's are also included.
The Effect of Data Scaling on Dual Prices and Sensitivity Analysis in Linear Programs
ERIC Educational Resources Information Center
Adlakha, V. G.; Vemuganti, R. R.
2007-01-01
In many practical situations scaling the data is necessary to solve linear programs. This note explores the relationships in translating the sensitivity analysis between the original and the scaled problems.
On the linear properties of the nonlinear radiative transfer problem
NASA Astrophysics Data System (ADS)
Pikichyan, H. V.
2016-11-01
In this report, we further expose the assertions made in nonlinear problem of reflection/transmission of radiation from a scattering/absorbing one-dimensional anisotropic medium of finite geometrical thickness, when both of its boundaries are illuminated by intense monochromatic radiative beams. The new conceptual element of well-defined, so-called, linear images is noteworthy. They admit a probabilistic interpretation. In the framework of nonlinear problem of reflection/transmission of radiation, we derive solution which is similar to linear case. That is, the solution is reduced to the linear combination of linear images. By virtue of the physical meaning, these functions describe the reflectivity and transmittance of the medium for a single photon or their beam of unit intensity, incident on one of the boundaries of the layer. Thereby the medium in real regime is still under the bilateral illumination by external exciting radiation of arbitrary intensity. To determine the linear images, we exploit three well known methods of (i) adding of layers, (ii) its limiting form, described by differential equations of invariant imbedding, and (iii) a transition to the, so-called, functional equations of the "Ambartsumyan's complete invariance".
Towards an ideal preconditioner for linearized Navier-Stokes problems
Murphy, M.F.
1996-12-31
Discretizing certain linearizations of the steady-state Navier-Stokes equations gives rise to nonsymmetric linear systems with indefinite symmetric part. We show that for such systems there exists a block diagonal preconditioner which gives convergence in three GMRES steps, independent of the mesh size and viscosity parameter (Reynolds number). While this {open_quotes}ideal{close_quotes} preconditioner is too expensive to be used in practice, it provides a useful insight into the problem. We then consider various approximations to the ideal preconditioner, and describe the eigenvalues of the preconditioned systems. Finally, we compare these preconditioners numerically, and present our conclusions.
User's manual for interactive LINEAR: A FORTRAN program to derive linear aircraft models
NASA Technical Reports Server (NTRS)
Antoniewicz, Robert F.; Duke, Eugene L.; Patterson, Brian P.
1988-01-01
An interactive FORTRAN program that provides the user with a powerful and flexible tool for the linearization of aircraft aerodynamic models is documented in this report. The program LINEAR numerically determines a linear system model using nonlinear equations of motion and a user-supplied linear or nonlinear aerodynamic model. The nonlinear equations of motion used are six-degree-of-freedom equations with stationary atmosphere and flat, nonrotating earth assumptions. The system model determined by LINEAR consists of matrices for both the state and observation equations. The program has been designed to allow easy selection and definition of the state, control, and observation variables to be used in a particular model.
Diffusion LMS for Multitask Problems With Local Linear Equality Constraints
NASA Astrophysics Data System (ADS)
Nassif, Roula; Richard, Cedric; Ferrari, Andre; Sayed, Ali H.
2017-10-01
We consider distributed multitask learning problems over a network of agents where each agent is interested in estimating its own parameter vector, also called task, and where the tasks at neighboring agents are related according to a set of linear equality constraints. Each agent possesses its own convex cost function of its parameter vector and a set of linear equality constraints involving its own parameter vector and the parameter vectors of its neighboring agents. We propose an adaptive stochastic algorithm based on the projection gradient method and diffusion strategies in order to allow the network to optimize the individual costs subject to all constraints. Although the derivation is carried out for linear equality constraints, the technique can be applied to other forms of convex constraints. We conduct a detailed mean-square-error analysis of the proposed algorithm and derive closed-form expressions to predict its learning behavior. We provide simulations to illustrate the theoretical findings. Finally, the algorithm is employed for solving two problems in a distributed manner: a minimum-cost flow problem over a network and a space-time varying field reconstruction problem.
Hlaing, Lwin Mar; Fahmida, Umi; Htet, Min Kyaw; Utomo, Budi; Firmansyah, Agus; Ferguson, Elaine L
2016-07-01
Poor feeding practices result in inadequate nutrient intakes in young children in developing countries. To improve practices, local food-based complementary feeding recommendations (CFR) are needed. This cross-sectional survey aimed to describe current food consumption patterns of 12-23-month-old Myanmar children (n 106) from Ayeyarwady region in order to identify nutrient requirements that are difficult to achieve using local foods and to formulate affordable and realistic CFR to improve dietary adequacy. Weekly food consumption patterns were assessed using a 12-h weighed dietary record, single 24-h recall and a 5-d food record. Food costs were estimated by market surveys. CFR were formulated by linear programming analysis using WHO Optifood software and evaluated among mothers (n 20) using trial of improved practices (TIP). Findings showed that Ca, Zn, niacin, folate and Fe were 'problem nutrients': nutrients that did not achieve 100 % recommended nutrient intake even when the diet was optimised. Chicken liver, anchovy and roselle leaves were locally available nutrient-dense foods that would fill these nutrient gaps. The final set of six CFR would ensure dietary adequacy for five of twelve nutrients at a minimal cost of 271 kyats/d (based on the exchange rate of 900 kyats/USD at the time of data collection: 3rd quarter of 2012), but inadequacies remained for niacin, folate, thiamin, Fe, Zn, Ca and vitamin B6. TIP showed that mothers believed liver and vegetables would cause worms and diarrhoea, but these beliefs could be overcome to successfully promote liver consumption. Therefore, an acceptable set of CFR were developed to improve the dietary practices of 12-23-month-old Myanmar children using locally available foods. Alternative interventions such as fortification, however, are still needed to ensure dietary adequacy of all nutrients.
An algorithm for the solution of dynamic linear programs
NASA Technical Reports Server (NTRS)
Psiaki, Mark L.
1989-01-01
The algorithm's objective is to efficiently solve Dynamic Linear Programs (DLP) by taking advantage of their special staircase structure. This algorithm constitutes a stepping stone to an improved algorithm for solving Dynamic Quadratic Programs, which, in turn, would make the nonlinear programming method of Successive Quadratic Programs more practical for solving trajectory optimization problems. The ultimate goal is to being trajectory optimization solution speeds into the realm of real-time control. The algorithm exploits the staircase nature of the large constraint matrix of the equality-constrained DLPs encountered when solving inequality-constrained DLPs by an active set approach. A numerically-stable, staircase QL factorization of the staircase constraint matrix is carried out starting from its last rows and columns. The resulting recursion is like the time-varying Riccati equation from multi-stage LQR theory. The resulting factorization increases the efficiency of all of the typical LP solution operations over that of a dense matrix LP code. At the same time numerical stability is ensured. The algorithm also takes advantage of dynamic programming ideas about the cost-to-go by relaxing active pseudo constraints in a backwards sweeping process. This further decreases the cost per update of the LP rank-1 updating procedure, although it may result in more changes of the active set that if pseudo constraints were relaxed in a non-stagewise fashion. The usual stability of closed-loop Linear/Quadratic optimally-controlled systems, if it carries over to strictly linear cost functions, implies that the saving due to reduced factor update effort may outweigh the cost of an increased number of updates. An aerospace example is presented in which a ground-to-ground rocket's distance is maximized. This example demonstrates the applicability of this class of algorithms to aerospace guidance. It also sheds light on the efficacy of the proposed pseudo constraint relaxation
Measurement problem in PROGRAM UNIVERSE
Noyes, H.P.; Gefwert, C.
1984-12-01
We present a discrete theory that meets the measurement problem in a new way. We generate a growing universe of bit strings, labeled by 2/sup 127/ + 136 strings organized by some representation of the closed, four level, combinatorial hierarchy, of bit-length N/sub 139/ greater than or equal to 139. The rest of the strings for each label, which grow in both length and number, are called addresses. The generating algorithm, called PROGRAM UNIVERSE, starts from a random choice between the two symbols ''0'' and ''1'' and grows (a) by discriminating between two randomly chosen strings and adjoining a novel result to the universe, or when the string so generated is not novel, by (b) adjoining a randomly chosen bit at the growing end of each string. We obtain, by appropriate definitions and interpretations, stable ''particles'' which satisfy the usual relativistic kinematics and quantized angular momentum without being localizable in a continuum space-time. The labeling scheme is congruent with the ''standard model'' of quarks and leptons with three generations, but for the problem at hand, the implementation of this aspect of the theory is unimportant. What matters most is that (a) these complicated ''particles'' have the periodicities familiar from relativistic ''deBroglie waves'' and resolve in a discrete way the ''wave-particle dualism'' and (b) can be ''touched'' by our discrete equivalent of ''soft photons'' in such a way as to follow, macroscopically, the usual Rutherford scattering trajectories with the associated bound states. Thus our theory could provide a discrete description of ''measurement'' in a way that allows no conceptual barrier between the ''micro'' and the ''macro'' worlds, if we are willing to base our physics on counting and exclude the ambiguities associated with the unobservable ''continuum''. 27 refs.
1983-08-01
earlier paper, our present analysis applies only to the symmetric linear complementarity problem . Various applications to a strictly convex quadratic...characterization requires no such constraint qualification as (F). There is yet another approach to apply an iterative method for solving the strictly convex ...described a Lagrangian relaxation algorithm for a constrained matrix problem which is formulated as a strictly convex separable quadratic program. They
Geodetic linear estimation technique and the norm choice problem
NASA Technical Reports Server (NTRS)
Dermanis, A.
1977-01-01
In this work the mathematical and probabilistic background of standard linear estimation techniques used in geodesy is clarified, and their interrelationship is revealed with the help of best approximation theory and the normal equations. Emphasis is given to the separation of the deterministic solution to the approximation problem from the probabilistic justification of the metric of the approximation. Least squares prediction has been related to deterministic (exact) collocation, and minimum error bound has been identified as a prediction optimality criterion in the latter. Criteria for the optimal choice of norm in Hilbert space collocation are proposed for gravimetric geodesy problems.
An analytically solvable eigenvalue problem for the linear elasticity equations.
Day, David Minot; Romero, Louis Anthony
2004-07-01
Analytic solutions are useful for code verification. Structural vibration codes approximate solutions to the eigenvalue problem for the linear elasticity equations (Navier's equations). Unfortunately the verification method of 'manufactured solutions' does not apply to vibration problems. Verification books (for example [2]) tabulate a few of the lowest modes, but are not useful for computations of large numbers of modes. A closed form solution is presented here for all the eigenvalues and eigenfunctions for a cuboid solid with isotropic material properties. The boundary conditions correspond physically to a greased wall.
The Solution of Linear Complementarity Problems on an Array Processor.
1981-01-01
WISCONSIN-MADISON MATHEMATICS RESEARCH CENTER THE SOLUTION OF LINEAR COMPLEMENTARITY PROBLEMS ON AN ARRAY PROCESSOR C. W. Cryer* ’ 1 , P. M. Flanders...8217, D. J. Hunt+ , S. F. Reddaway+ , and J. Stansbury**’ 1 Technical Summary Report #2170 January 1981 ABSTRACT The Distributed Array Processor (DAP...manufactured by International Computers Limited is an array of 1 -bit 200-nanosecond processors. The Pilot DAP on which the present work was done is a 32
Linear programming based on neural networks for radiotherapy treatment planning.
Wu, X; Zhu, Y; Luo, L
2000-03-01
In this paper, we propose a neural network model for linear programming that is designed to optimize radiotherapy treatment planning (RTP). This kind of neural network can be easily implemented by using a kind of 'neural' electronic system in order to obtain an optimization solution in real time. We first give an introduction to the RTP problem and construct a non-constraint objective function for the neural network model. We adopt a gradient algorithm to minimize the objective function and design the structure of the neural network for RTP. Compared to traditional linear programming methods, this neural network model can reduce the time needed for convergence, the size of problems (i.e., the number of variables to be searched) and the number of extra slack and surplus variables needed. We obtained a set of optimized beam weights that result in a better dose distribution as compared to that obtained using the simplex algorithm under the same initial condition. The example presented in this paper shows that this model is feasible in three-dimensional RTP.
Assembling networks of microbial genomes using linear programming
2010-01-01
Background Microbial genomes exhibit complex sets of genetic affinities due to lateral genetic transfer. Assessing the relative contributions of parent-to-offspring inheritance and gene sharing is a vital step in understanding the evolutionary origins and modern-day function of an organism, but recovering and showing these relationships is a challenging problem. Results We have developed a new approach that uses linear programming to find between-genome relationships, by treating tables of genetic affinities (here, represented by transformed BLAST e-values) as an optimization problem. Validation trials on simulated data demonstrate the effectiveness of the approach in recovering and representing vertical and lateral relationships among genomes. Application of the technique to a set comprising Aquifex aeolicus and 75 other thermophiles showed an important role for large genomes as 'hubs' in the gene sharing network, and suggested that genes are preferentially shared between organisms with similar optimal growth temperatures. We were also able to discover distinct and common genetic contributors to each sequenced representative of genus Pseudomonas. Conclusions The linear programming approach we have developed can serve as an effective inference tool in its own right, and can be an efficient first step in a more-intensive phylogenomic analysis. PMID:21092133
Assembling networks of microbial genomes using linear programming.
Holloway, Catherine; Beiko, Robert G
2010-11-20
Microbial genomes exhibit complex sets of genetic affinities due to lateral genetic transfer. Assessing the relative contributions of parent-to-offspring inheritance and gene sharing is a vital step in understanding the evolutionary origins and modern-day function of an organism, but recovering and showing these relationships is a challenging problem. We have developed a new approach that uses linear programming to find between-genome relationships, by treating tables of genetic affinities (here, represented by transformed BLAST e-values) as an optimization problem. Validation trials on simulated data demonstrate the effectiveness of the approach in recovering and representing vertical and lateral relationships among genomes. Application of the technique to a set comprising Aquifex aeolicus and 75 other thermophiles showed an important role for large genomes as 'hubs' in the gene sharing network, and suggested that genes are preferentially shared between organisms with similar optimal growth temperatures. We were also able to discover distinct and common genetic contributors to each sequenced representative of genus Pseudomonas. The linear programming approach we have developed can serve as an effective inference tool in its own right, and can be an efficient first step in a more-intensive phylogenomic analysis.
VARAN: A Linear Model Variance Analysis Program.
ERIC Educational Resources Information Center
Hall, Charles E.; And Others
This memorandum is the manual for the VARAN (VARiance ANalysis) program, which is the latest addition to a series of computer programs for multivariate analysis of variance. As with earlier programs, analysis of variance, univariate and multivariate, is the main target of the program. Correlation analysis of all types is available with printout in…
A Teaching Tool for Linear Programming
1993-07-01
U I Bibliography U Anton, Howard. Elementary Linear Algebra . 5th ed. New York: John Wiley & Sons, 1973.I...Richard 0. Jr. Elementary Linear Algebra with Applications. 2nd ed. San Diego: Harcourt Brace Jovanovich, 1991.I I Hillier, Frederick S. Pnd Gerald
Split diversity in constrained conservation prioritization using integer linear programming.
Chernomor, Olga; Minh, Bui Quang; Forest, Félix; Klaere, Steffen; Ingram, Travis; Henzinger, Monika; von Haeseler, Arndt
2015-01-01
Phylogenetic diversity (PD) is a measure of biodiversity based on the evolutionary history of species. Here, we discuss several optimization problems related to the use of PD, and the more general measure split diversity (SD), in conservation prioritization.Depending on the conservation goal and the information available about species, one can construct optimization routines that incorporate various conservation constraints. We demonstrate how this information can be used to select sets of species for conservation action. Specifically, we discuss the use of species' geographic distributions, the choice of candidates under economic pressure, and the use of predator-prey interactions between the species in a community to define viability constraints.Despite such optimization problems falling into the area of NP hard problems, it is possible to solve them in a reasonable amount of time using integer programming. We apply integer linear programming to a variety of models for conservation prioritization that incorporate the SD measure.We exemplarily show the results for two data sets: the Cape region of South Africa and a Caribbean coral reef community. Finally, we provide user-friendly software at http://www.cibiv.at/software/pda.
Moryakov, A. V. Pylyov, S. S.
2012-12-15
This paper presents the formulation of the problem and the methodical approach for solving large systems of linear differential equations describing nonstationary processes with the use of CUDA technology; this approach is implemented in the ANGEL program. Results for a test problem on transport of radioactive products over loops of a nuclear power plant are given. The possibilities for the use of the ANGEL program for solving various problems that simulate arbitrary nonstationary processes are discussed.
NASA Technical Reports Server (NTRS)
Bowman, L. M.
1984-01-01
An interactive steady state frequency response computer program with graphics is documented. Single or multiple forces may be applied to the structure using a modal superposition approach to calculate response. The method can be reapplied to linear, proportionally damped structures in which the damping may be viscous or structural. The theoretical approach and program organization are described. Example problems, user instructions, and a sample interactive session are given to demonstate the program's capability in solving a variety of problems.
A Sawmill Manager Adapts To Change With Linear Programming
George F. Dutrow; James E. Granskog
1973-01-01
Linear programming provides guidelines for increasing sawmill capacity and flexibility and for determining stumpagepurchasing strategy. The operator of a medium-sized sawmill implemented improvements suggested by linear programming analysis; results indicate a 45 percent increase in revenue and a 36 percent hike in volume processed.
Accurate construction of consensus genetic maps via integer linear programming.
Wu, Yonghui; Close, Timothy J; Lonardi, Stefano
2011-01-01
We study the problem of merging genetic maps, when the individual genetic maps are given as directed acyclic graphs. The computational problem is to build a consensus map, which is a directed graph that includes and is consistent with all (or, the vast majority of) the markers in the input maps. However, when markers in the individual maps have ordering conflicts, the resulting consensus map will contain cycles. Here, we formulate the problem of resolving cycles in the context of a parsimonious paradigm that takes into account two types of errors that may be present in the input maps, namely, local reshuffles and global displacements. The resulting combinatorial optimization problem is, in turn, expressed as an integer linear program. A fast approximation algorithm is proposed, and an additional speedup heuristic is developed. Our algorithms were implemented in a software tool named MERGEMAP which is freely available for academic use. An extensive set of experiments shows that MERGEMAP consistently outperforms JOINMAP, which is the most popular tool currently available for this task, both in terms of accuracy and running time. MERGEMAP is available for download at http://www.cs.ucr.edu/~yonghui/mgmap.html.
Rees algebras, Monomial Subrings and Linear Optimization Problems
NASA Astrophysics Data System (ADS)
Dupont, Luis A.
2010-06-01
In this thesis we are interested in studying algebraic properties of monomial algebras, that can be linked to combinatorial structures, such as graphs and clutters, and to optimization problems. A goal here is to establish bridges between commutative algebra, combinatorics and optimization. We study the normality and the Gorenstein property-as well as the canonical module and the a-invariant-of Rees algebras and subrings arising from linear optimization problems. In particular, we study algebraic properties of edge ideals and algebras associated to uniform clutters with the max-flow min-cut property or the packing property. We also study algebraic properties of symbolic Rees algebras of edge ideals of graphs, edge ideals of clique clutters of comparability graphs, and Stanley-Reisner rings.
NASA Astrophysics Data System (ADS)
Indarsih, Indrati, Ch. Rini
2016-02-01
In this paper, we define variance of the fuzzy random variables through alpha level. We have a theorem that can be used to know that the variance of fuzzy random variables is a fuzzy number. We have a multi-objective linear programming (MOLP) with fuzzy random of objective function coefficients. We will solve the problem by variance approach. The approach transform the MOLP with fuzzy random of objective function coefficients into MOLP with fuzzy of objective function coefficients. By weighted methods, we have linear programming with fuzzy coefficients and we solve by simplex method for fuzzy linear programming.
Micosoft Excel Sensitivity Analysis for Linear and Stochastic Program Feed Formulation
USDA-ARS?s Scientific Manuscript database
Sensitivity analysis is a part of mathematical programming solutions and is used in making nutritional and economic decisions for a given feed formulation problem. The terms, shadow price and reduced cost, are familiar linear program (LP) terms to feed formulators. Because of the nonlinear nature of...
1991-10-31
Problems, Mathematical Programming Studies, 48:1, 1-18. R. E. Marsten, 1989. User’s Manual for: OB1/XMP, Interior Point Methods for Linear Programming. R. E...Industrial Dr. Istvan Maros E.T.S. Ingenieros Industriales Computer and Automation Institute Jose Gutierrez Abascal, 2 Hungarian Academy of Sciences E
Linear Fresnel lens photovoltaic concentrator program
Kull, J.; Maraschin, R.; Rafinejad, D.; Spencer, R.; Sutton, G.
1983-08-01
This report describes Acurex Corporation's design of a linear Fresnel lens Photovoltaic Concentrator Panel. The panel consists of four concentrator modules in an integrated structure. Each module is 10 ft long and has a 39.85 in aperture. The solar cell's active width is 0.90 in. and the cell-lens edge spacing is 23.39 in. There are 58 cells per module. A prototype panel was built and tested. Test results showed a peak electrical efficiency of 10.5% at the operating conditions of 800 W/m/sup 2/ insolation and 90/sup 0/F coolant temperature. The prototype exhibits the manufacturing and assembly concepts developed.
Mixed integer linear programming for maximum-parsimony phylogeny inference.
Sridhar, Srinath; Lam, Fumei; Blelloch, Guy E; Ravi, R; Schwartz, Russell
2008-01-01
Reconstruction of phylogenetic trees is a fundamental problem in computational biology. While excellent heuristic methods are available for many variants of this problem, new advances in phylogeny inference will be required if we are to be able to continue to make effective use of the rapidly growing stores of variation data now being gathered. In this paper, we present two integer linear programming (ILP) formulations to find the most parsimonious phylogenetic tree from a set of binary variation data. One method uses a flow-based formulation that can produce exponential numbers of variables and constraints in the worst case. The method has, however, proven extremely efficient in practice on datasets that are well beyond the reach of the available provably efficient methods, solving several large mtDNA and Y-chromosome instances within a few seconds and giving provably optimal results in times competitive with fast heuristics than cannot guarantee optimality. An alternative formulation establishes that the problem can be solved with a polynomial-sized ILP. We further present a web server developed based on the exponential-sized ILP that performs fast maximum parsimony inferences and serves as a front end to a database of precomputed phylogenies spanning the human genome.
Measuring Astronomical Distances with Linear Programming
ERIC Educational Resources Information Center
Narain, Akshar
2015-01-01
A few years ago it was suggested that the distance to celestial bodies could be computed by tracking their position over about 24 hours and then solving a regression problem. One only needed to use inexpensive telescopes, cameras, and astrometry tools, and the experiment could be done from one's backyard. However, it is not obvious to an amateur…
Measuring Astronomical Distances with Linear Programming
ERIC Educational Resources Information Center
Narain, Akshar
2015-01-01
A few years ago it was suggested that the distance to celestial bodies could be computed by tracking their position over about 24 hours and then solving a regression problem. One only needed to use inexpensive telescopes, cameras, and astrometry tools, and the experiment could be done from one's backyard. However, it is not obvious to an amateur…
Optimized constraints for the linearized geoacoustic inverse problem.
Ballard, Megan S; Becker, Kyle M
2011-02-01
A geoacoustic inversion scheme to estimate the depth-dependent sound speed characteristics of the shallow-water waveguide is presented. The approach is based on the linearized perturbative technique developed by Rajan et al. [J. Acoust. Soc. Am. 82, 998-1017 (1987)]. This method is applied by assuming a background starting model for the environment that includes both the water column and the seabed. Typically, the water column properties are assumed to be known and held fixed in the inversion. Successful application of the perturbative inverse technique lies in handling issues of stability and uniqueness associated with solving a discrete ill-posed problem. Conventionally, such problems are regularized, a procedure which results in a smooth solution. Past applications of this inverse technique have been restricted to cases for which the water column sound speed profile was known and sound speed in the seabed could be approximated by a smooth profile. In this work, constraints that are better suited to specific aspects of the geoacoustic inverse problem are applied. These techniques expand on the original application of the perturbative inverse technique by including the water column sound speed profile in the solution and by allowing for discontinuities in the seabed sound speed profile.
Linearization of the boundary-layer equations of the minimum time-to-climb problem
NASA Technical Reports Server (NTRS)
Ardema, M. D.
1979-01-01
Ardema (1974) has formally linearized the two-point boundary value problem arising from a general optimal control problem, and has reviewed the known stability properties of such a linear system. In the present paper, Ardema's results are applied to the minimum time-to-climb problem. The linearized zeroth-order boundary layer equations of the problem are derived and solved.
First integrals for the Kepler problem with linear drag
NASA Astrophysics Data System (ADS)
Margheri, Alessandro; Ortega, Rafael; Rebelo, Carlota
2017-01-01
In this work we consider the Kepler problem with linear drag, and prove the existence of a continuous vector-valued first integral, obtained taking the limit as t→ +∞ of the Runge-Lenz vector. The norm of this first integral can be interpreted as an asymptotic eccentricity e_{∞} with 0≤ e_{∞} ≤ 1. The orbits satisfying e_{∞} <1 approach the singularity by an elliptic spiral and the corresponding solutions x(t)=r(t)e^{iθ (t)} have a norm r( t) that goes to zero like a negative exponential and an argument θ (t) that goes to infinity like a positive exponential. In particular, the difference between consecutive times of passage through the pericenter, say T_{n+1} -T_n, goes to zero as 1/n.
Using parallel banded linear system solvers in generalized eigenvalue problems
NASA Technical Reports Server (NTRS)
Zhang, Hong; Moss, William F.
1993-01-01
Subspace iteration is a reliable and cost effective method for solving positive definite banded symmetric generalized eigenproblems, especially in the case of large scale problems. This paper discusses an algorithm that makes use of two parallel banded solvers in subspace iteration. A shift is introduced to decompose the banded linear systems into relatively independent subsystems and to accelerate the iterations. With this shift, an eigenproblem is mapped efficiently into the memories of a multiprocessor and a high speed-up is obtained for parallel implementations. An optimal shift is a shift that balances total computation and communication costs. Under certain conditions, we show how to estimate an optimal shift analytically using the decay rate for the inverse of a banded matrix, and how to improve this estimate. Computational results on iPSC/2 and iPSC/860 multiprocessors are presented.
SUBOPT: A CAD program for suboptimal linear regulators
NASA Technical Reports Server (NTRS)
Fleming, P. J.
1985-01-01
An interactive software package which provides design solutions for both standard linear quadratic regulator (LQR) and suboptimal linear regulator problems is described. Intended for time-invariant continuous systems, the package is easily modified to include sampled-data systems. LQR designs are obtained by established techniques while the large class of suboptimal problems containing controller and/or performance index options is solved using a robust gradient minimization technique. Numerical examples demonstrate features of the package and recent developments are described.
Algorithm 937: MINRES-QLP for Symmetric and Hermitian Linear Equations and Least-Squares Problems
Choi, Sou-Cheng T.; Saunders, Michael A.
2014-01-01
We describe algorithm MINRES-QLP and its FORTRAN 90 implementation for solving symmetric or Hermitian linear systems or least-squares problems. If the system is singular, MINRES-QLP computes the unique minimum-length solution (also known as the pseudoinverse solution), which generally eludes MINRES. In all cases, it overcomes a potential instability in the original MINRES algorithm. A positive-definite pre-conditioner may be supplied. Our FORTRAN 90 implementation illustrates a design pattern that allows users to make problem data known to the solver but hidden and secure from other program units. In particular, we circumvent the need for reverse communication. Example test programs input and solve real or complex problems specified in Matrix Market format. While we focus here on a FORTRAN 90 implementation, we also provide and maintain MATLAB versions of MINRES and MINRES-QLP. PMID:25328255
The RANDOM computer program: A linear congruential random number generator
NASA Technical Reports Server (NTRS)
Miles, R. F., Jr.
1986-01-01
The RANDOM Computer Program is a FORTRAN program for generating random number sequences and testing linear congruential random number generators (LCGs). The linear congruential form of random number generator is discussed, and the selection of parameters of an LCG for a microcomputer described. This document describes the following: (1) The RANDOM Computer Program; (2) RANDOM.MOD, the computer code needed to implement an LCG in a FORTRAN program; and (3) The RANCYCLE and the ARITH Computer Programs that provide computational assistance in the selection of parameters for an LCG. The RANDOM, RANCYCLE, and ARITH Computer Programs are written in Microsoft FORTRAN for the IBM PC microcomputer and its compatibles. With only minor modifications, the RANDOM Computer Program and its LCG can be run on most micromputers or mainframe computers.
Learning oncogenetic networks by reducing to mixed integer linear programming.
Shahrabi Farahani, Hossein; Lagergren, Jens
2013-01-01
Cancer can be a result of accumulation of different types of genetic mutations such as copy number aberrations. The data from tumors are cross-sectional and do not contain the temporal order of the genetic events. Finding the order in which the genetic events have occurred and progression pathways are of vital importance in understanding the disease. In order to model cancer progression, we propose Progression Networks, a special case of Bayesian networks, that are tailored to model disease progression. Progression networks have similarities with Conjunctive Bayesian Networks (CBNs) [1],a variation of Bayesian networks also proposed for modeling disease progression. We also describe a learning algorithm for learning Bayesian networks in general and progression networks in particular. We reduce the hard problem of learning the Bayesian and progression networks to Mixed Integer Linear Programming (MILP). MILP is a Non-deterministic Polynomial-time complete (NP-complete) problem for which very good heuristics exists. We tested our algorithm on synthetic and real cytogenetic data from renal cell carcinoma. We also compared our learned progression networks with the networks proposed in earlier publications. The software is available on the website https://bitbucket.org/farahani/diprog.
1980-10-01
THE SOLUTION OF LINEAR COMPLEMENTARITY PROBLEMS ARISING FROM FREE BOUNDARY PROBLEMS Achi Brandt*’ ( 1 ) and Colin W. Cryer’ (2 1.1 INTRODUCTION...University of Wisconsin-Madison, Madison, Madison, WI 53706. ( 1 )Sponsored by the United States Army under Contract No. DAAG29-80-C-0041. (2)Sponsored by...multi- plying (1.3a) by - 1 . For example, if t is the Laplace operator in R 2 , then a possible choice for L would be the classical five-point difference
Problems, Perplexities, and Politics of Program Evaluation.
ERIC Educational Resources Information Center
Schneider, Gail Thierbach
All educational evaluations share common problems, perplexities, and political considerations. Logistic problems include incomplete definition of purpose, unclear timelines and personnel allocations, inadequate support services, and the lack of a program plan. Interpersonal dynamics and conflicts plus unwieldy committee structures are perplexities…
Linear Programming for Vocational Education Planning. Interim Report.
ERIC Educational Resources Information Center
Young, Robert C.; And Others
The purpose of the paper is to define for potential users of vocational education management information systems a quantitative analysis technique and its utilization to facilitate more effective planning of vocational education programs. Defining linear programming (LP) as a management technique used to solve complex resource allocation problems…
Planning Student Flow with Linear Programming: A Tunisian Case Study.
ERIC Educational Resources Information Center
Bezeau, Lawrence
A student flow model in linear programming format, designed to plan the movement of students into secondary and university programs in Tunisia, is described. The purpose of the plan is to determine a sufficient number of graduating students that would flow back into the system as teachers or move into the labor market to meet fixed manpower…
Problem Solving. Workplace Education Program Curriculum.
ERIC Educational Resources Information Center
Burkhart, Jennifer
The BUILD Program (Businesses United to Increase Literacy Development) was conducted from June 1991 through December 1992 as a cooperative workplace literacy program joining Arapahoe Community College and four companies in Littleton, Colorado. This document consists of three modules for the problem-solving and computer learning systems classes of…
FSILP: fuzzy-stochastic-interval linear programming for supporting municipal solid waste management.
Li, Pu; Chen, Bing
2011-04-01
Although many studies on municipal solid waste management (MSW management) were conducted under uncertain conditions of fuzzy, stochastic, and interval coexistence, the solution to the conventional linear programming problems of integrating fuzzy method with the other two was inefficient. In this study, a fuzzy-stochastic-interval linear programming (FSILP) method is developed by integrating Nguyen's method with conventional linear programming for supporting municipal solid waste management. The Nguyen's method was used to convert the fuzzy and fuzzy-stochastic linear programming problems into the conventional linear programs, by measuring the attainment values of fuzzy numbers and/or fuzzy random variables, as well as superiority and inferiority between triangular fuzzy numbers/triangular fuzzy-stochastic variables. The developed method can effectively tackle uncertainties described in terms of probability density functions, fuzzy membership functions, and discrete intervals. Moreover, the method can also improve upon the conventional interval fuzzy programming and two-stage stochastic programming approaches, with advantageous capabilities that are easily achieved with fewer constraints and significantly reduces consumption time. The developed model was applied to a case study of municipal solid waste management system in a city. The results indicated that reasonable solutions had been generated. The solution can help quantify the relationship between the change of system cost and the uncertainties, which could support further analysis of tradeoffs between the waste management cost and the system failure risk.
NASA Technical Reports Server (NTRS)
Frost, Susan A.; Bodson, Marc; Acosta, Diana M.
2009-01-01
The Next Generation (NextGen) transport aircraft configurations being investigated as part of the NASA Aeronautics Subsonic Fixed Wing Project have more control surfaces, or control effectors, than existing transport aircraft configurations. Conventional flight control is achieved through two symmetric elevators, two antisymmetric ailerons, and a rudder. The five effectors, reduced to three command variables, produce moments along the three main axes of the aircraft and enable the pilot to control the attitude and flight path of the aircraft. The NextGen aircraft will have additional redundant control effectors to control the three moments, creating a situation where the aircraft is over-actuated and where a simple relationship does not exist anymore between the required effector deflections and the desired moments. NextGen flight controllers will incorporate control allocation algorithms to determine the optimal effector commands and attain the desired moments, taking into account the effector limits. Approaches to solving the problem using linear programming and quadratic programming algorithms have been proposed and tested. It is of great interest to understand their relative advantages and disadvantages and how design parameters may affect their properties. In this paper, we investigate the sensitivity of the effector commands with respect to the desired moments and show on some examples that the solutions provided using the l2 norm of quadratic programming are less sensitive than those using the l1 norm of linear programming.
Application of linear programming techniques for controlling linear dynamic plants in real time
NASA Astrophysics Data System (ADS)
Gabasov, R.; Kirillova, F. M.; Ha, Vo Thi Thanh
2016-03-01
The problem of controlling a linear dynamic plant in real time given its nondeterministic model and imperfect measurements of the inputs and outputs is considered. The concepts of current distributions of the initial state and disturbance parameters are introduced. The method for the implementation of disclosable loop using the separation principle is described. The optimal control problem under uncertainty conditions is reduced to the problems of optimal observation, optimal identification, and optimal control of the deterministic system. To extend the domain where a solution to the optimal control problem under uncertainty exists, a two-stage optimal control method is proposed. Results are illustrated using a dynamic plant of the fourth order.
The fastclime Package for Linear Programming and Large-Scale Precision Matrix Estimation in R
Pang, Haotian; Liu, Han; Vanderbei, Robert
2014-01-01
We develop an R package fastclime for solving a family of regularized linear programming (LP) problems. Our package efficiently implements the parametric simplex algorithm, which provides a scalable and sophisticated tool for solving large-scale linear programs. As an illustrative example, one use of our LP solver is to implement an important sparse precision matrix estimation method called CLIME (Constrained L1 Minimization Estimator). Compared with existing packages for this problem such as clime and flare, our package has three advantages: (1) it efficiently calculates the full piecewise-linear regularization path; (2) it provides an accurate dual certificate as stopping criterion; (3) it is completely coded in C and is highly portable. This package is designed to be useful to statisticians and machine learning researchers for solving a wide range of problems. PMID:25620890
The fastclime Package for Linear Programming and Large-Scale Precision Matrix Estimation in R.
Pang, Haotian; Liu, Han; Vanderbei, Robert
2014-02-01
We develop an R package fastclime for solving a family of regularized linear programming (LP) problems. Our package efficiently implements the parametric simplex algorithm, which provides a scalable and sophisticated tool for solving large-scale linear programs. As an illustrative example, one use of our LP solver is to implement an important sparse precision matrix estimation method called CLIME (Constrained L1 Minimization Estimator). Compared with existing packages for this problem such as clime and flare, our package has three advantages: (1) it efficiently calculates the full piecewise-linear regularization path; (2) it provides an accurate dual certificate as stopping criterion; (3) it is completely coded in C and is highly portable. This package is designed to be useful to statisticians and machine learning researchers for solving a wide range of problems.
Optimal control of a satellite-robot system using direct collocation with non-linear programming
NASA Astrophysics Data System (ADS)
Coverstone-Carroll, V. L.; Wilkey, N. M.
1995-08-01
The non-holonomic behavior of a satellite-robot system is used to develop the system's equations of motion. The resulting non-linear differential equations are transformed into a non-linear programming problem using direct collocation. The link rates of the robot are minimized along optimal reorientations. Optimal solutions to several maneuvers are obtained and the results are interpreted to gain an understanding of the satellite-robot dynamics.
Dynamic Programming for Structured Continuous Markov Decision Problems
NASA Technical Reports Server (NTRS)
Dearden, Richard; Meuleau, Nicholas; Washington, Richard; Feng, Zhengzhu
2004-01-01
We describe an approach for exploiting structure in Markov Decision Processes with continuous state variables. At each step of the dynamic programming, the state space is dynamically partitioned into regions where the value function is the same throughout the region. We first describe the algorithm for piecewise constant representations. We then extend it to piecewise linear representations, using techniques from POMDPs to represent and reason about linear surfaces efficiently. We show that for complex, structured problems, our approach exploits the natural structure so that optimal solutions can be computed efficiently.
A linear-programming approach to temporal reasoning
Jonsson, P.; Baeckstroem, C.
1996-12-31
We present a new formalism, Horn Disjunctive Linear Relations (Horn DLRs), for reasoning about temporal constraints. We prove that deciding satisfiability of sets of Horn DLRs is polynomial by exhibiting an algorithm based upon linear programming. Furthermore, we prove that most other approaches to tractable temporal constraint reasoning can be encoded as Horn DLRs, including the ORD-Horn algebra and most methods for purely quantitative reasoning.
NASA Astrophysics Data System (ADS)
Zimmermann, Karl-Heinz; Achtziger, Wolfgang
2001-09-01
The size of a systolic array synthesized from a uniform recurrence equation, whose computations are mapped by a linear function to the processors, matches the problem size. In practice, however, there exist several limiting factors on the array size. There are two dual schemes available to derive arrays of smaller size from large-size systolic arrays based on the partitioning of the large-size arrays into subarrays. In LSGP, the subarrays are clustered one-to-one into the processors of a small-size array, while in LPGS, the subarrays are serially assigned to a reduced-size array. In this paper, we propose a common methodology for both LSGP and LPGS based on polyhedral partitionings of large-size k-dimensional systolic arrays which are synthesized from n-dimensional uniform recurrences by linear mappings for allocation and timing. In particular, we address the optimization problem of finding optimal piecewise linear timing functions for small-size arrays. These are mappings composed of linear timing functions for the computations of the subarrays. We study a continuous approximation of this problem by passing from piecewise linear to piecewise quasi-linear timing functions. The resultant problem formulation is then a quadratic programming problem which can be solved by standard algorithms for nonlinear optimization problems.
An Instructional Note on Linear Programming--A Pedagogically Sound Approach.
ERIC Educational Resources Information Center
Mitchell, Richard
1998-01-01
Discusses the place of linear programming in college curricula and the advantages of using linear-programming software. Lists important characteristics of computer software used in linear programming for more effective teaching and learning. (ASK)
A Mixed Integer Linear Program for Airport Departure Scheduling
NASA Technical Reports Server (NTRS)
Gupta, Gautam; Jung, Yoon Chul
2009-01-01
Aircraft departing from an airport are subject to numerous constraints while scheduling departure times. These constraints include wake-separation constraints for successive departures, miles-in-trail separation for aircraft bound for the same departure fixes, and time-window or prioritization constraints for individual flights. Besides these, emissions as well as increased fuel consumption due to inefficient scheduling need to be included. Addressing all the above constraints in a single framework while allowing for resequencing of the aircraft using runway queues is critical to the implementation of the Next Generation Air Transport System (NextGen) concepts. Prior work on airport departure scheduling has addressed some of the above. However, existing methods use pre-determined runway queues, and schedule aircraft from these departure queues. The source of such pre-determined queues is not explicit, and could potentially be a subjective controller input. Determining runway queues and scheduling within the same framework would potentially result in better scheduling. This paper presents a mixed integer linear program (MILP) for the departure-scheduling problem. The program takes as input the incoming sequence of aircraft for departure from a runway, along with their earliest departure times and an optional prioritization scheme based on time-window of departure for each aircraft. The program then assigns these aircraft to the available departure queues and schedules departure times, explicitly considering wake separation and departure fix restrictions to minimize total delay for all aircraft. The approach is generalized and can be used in a variety of situations, and allows for aircraft prioritization based on operational as well as environmental considerations. We present the MILP in the paper, along with benefits over the first-come-first-serve (FCFS) scheme for numerous randomized problems based on real-world settings. The MILP results in substantially reduced
Dense image registration through MRFs and efficient linear programming.
Glocker, Ben; Komodakis, Nikos; Tziritas, Georgios; Navab, Nassir; Paragios, Nikos
2008-12-01
In this paper, we introduce a novel and efficient approach to dense image registration, which does not require a derivative of the employed cost function. In such a context, the registration problem is formulated using a discrete Markov random field objective function. First, towards dimensionality reduction on the variables we assume that the dense deformation field can be expressed using a small number of control points (registration grid) and an interpolation strategy. Then, the registration cost is expressed using a discrete sum over image costs (using an arbitrary similarity measure) projected on the control points, and a smoothness term that penalizes local deviations on the deformation field according to a neighborhood system on the grid. Towards a discrete approach, the search space is quantized resulting in a fully discrete model. In order to account for large deformations and produce results on a high resolution level, a multi-scale incremental approach is considered where the optimal solution is iteratively updated. This is done through successive morphings of the source towards the target image. Efficient linear programming using the primal dual principles is considered to recover the lowest potential of the cost function. Very promising results using synthetic data with known deformations and real data demonstrate the potentials of our approach.
Maximum likelihood pedigree reconstruction using integer linear programming.
Cussens, James; Bartlett, Mark; Jones, Elinor M; Sheehan, Nuala A
2013-01-01
Large population biobanks of unrelated individuals have been highly successful in detecting common genetic variants affecting diseases of public health concern. However, they lack the statistical power to detect more modest gene-gene and gene-environment interaction effects or the effects of rare variants for which related individuals are ideally required. In reality, most large population studies will undoubtedly contain sets of undeclared relatives, or pedigrees. Although a crude measure of relatedness might sometimes suffice, having a good estimate of the true pedigree would be much more informative if this could be obtained efficiently. Relatives are more likely to share longer haplotypes around disease susceptibility loci and are hence biologically more informative for rare variants than unrelated cases and controls. Distant relatives are arguably more useful for detecting variants with small effects because they are less likely to share masking environmental effects. Moreover, the identification of relatives enables appropriate adjustments of statistical analyses that typically assume unrelatedness. We propose to exploit an integer linear programming optimisation approach to pedigree learning, which is adapted to find valid pedigrees by imposing appropriate constraints. Our method is not restricted to small pedigrees and is guaranteed to return a maximum likelihood pedigree. With additional constraints, we can also search for multiple high-probability pedigrees and thus account for the inherent uncertainty in any particular pedigree reconstruction. The true pedigree is found very quickly by comparison with other methods when all individuals are observed. Extensions to more complex problems seem feasible. © 2012 Wiley Periodicals, Inc.
Accommodation of practical constraints by a linear programming jet select. [for Space Shuttle
NASA Technical Reports Server (NTRS)
Bergmann, E.; Weiler, P.
1983-01-01
An experimental spacecraft control system will be incorporated into the Space Shuttle flight software and exercised during a forthcoming mission to evaluate its performance and handling qualities. The control system incorporates a 'phase space' control law to generate rate change requests and a linear programming jet select to compute jet firings. Posed as a linear programming problem, jet selection must represent the rate change request as a linear combination of jet acceleration vectors where the coefficients are the jet firing times, while minimizing the fuel expended in satisfying that request. This problem is solved in real time using a revised Simplex algorithm. In order to implement the jet selection algorithm in the Shuttle flight control computer, it was modified to accommodate certain practical features of the Shuttle such as limited computer throughput, lengthy firing times, and a large number of control jets. To the authors' knowledge, this is the first such application of linear programming. It was made possible by careful consideration of the jet selection problem in terms of the properties of linear programming and the Simplex algorithm. These modifications to the jet select algorithm may by useful for the design of reaction controlled spacecraft.
A new one-layer neural network for linear and quadratic programming.
Gao, Xingbao; Liao, Li-Zhi
2010-06-01
In this paper, we present a new neural network for solving linear and quadratic programming problems in real time by introducing some new vectors. The proposed neural network is stable in the sense of Lyapunov and can converge to an exact optimal solution of the original problem when the objective function is convex on the set defined by equality constraints. Compared with existing one-layer neural networks for quadratic programming problems, the proposed neural network has the least neurons and requires weak stability conditions. The validity and transient behavior of the proposed neural network are demonstrated by some simulation results.
The intelligence of dual simplex method to solve linear fractional fuzzy transportation problem.
Narayanamoorthy, S; Kalyani, S
2015-01-01
An approach is presented to solve a fuzzy transportation problem with linear fractional fuzzy objective function. In this proposed approach the fractional fuzzy transportation problem is decomposed into two linear fuzzy transportation problems. The optimal solution of the two linear fuzzy transportations is solved by dual simplex method and the optimal solution of the fractional fuzzy transportation problem is obtained. The proposed method is explained in detail with an example.
The Intelligence of Dual Simplex Method to Solve Linear Fractional Fuzzy Transportation Problem
Narayanamoorthy, S.; Kalyani, S.
2015-01-01
An approach is presented to solve a fuzzy transportation problem with linear fractional fuzzy objective function. In this proposed approach the fractional fuzzy transportation problem is decomposed into two linear fuzzy transportation problems. The optimal solution of the two linear fuzzy transportations is solved by dual simplex method and the optimal solution of the fractional fuzzy transportation problem is obtained. The proposed method is explained in detail with an example. PMID:25810713
Problem-Solving Transfer Among Programming Languages
1990-06-04
stable from programming in the first language to in the second. In other words, the transfer on subsequent drafts was mainly manifested as fewer drafts...substantial transfer from solving a problem in the first language (LISP or PROLOG) to solving it in the second language (PROLOG or LISP) in terms of time...transfer a lot of the algorithmic knowledge gained from programming in the first language to in the second. We will refer this type of transfer as
Linear combination reading program for capture gamma rays
Tanner, Allan B.
1971-01-01
This program computes a weighting function, Qj, which gives a scalar output value of unity when applied to the spectrum of a desired element and a minimum value (considering statistics) when applied to spectra of materials not containing the desired element. Intermediate values are obtained for materials containing the desired element, in proportion to the amount of the element they contain. The program is written in the BASIC language in a format specific to the Hewlett-Packard 2000A Time-Sharing System, and is an adaptation of an earlier program for linear combination reading for X-ray fluorescence analysis (Tanner and Brinkerhoff, 1971). Following the program is a sample run from a study of the application of the linear combination technique to capture-gamma-ray analysis for calcium (report in preparation).
THE SEPARATION OF URANIUM ISOTOPES BY GASEOUS DIFFUSION: A LINEAR PROGRAMMING MODEL,
URANIUM, ISOTOPE SEPARATION), (*GASEOUS DIFFUSION SEPARATION, LINEAR PROGRAMMING ), (* LINEAR PROGRAMMING , GASEOUS DIFFUSION SEPARATION), MATHEMATICAL MODELS, GAS FLOW, NUCLEAR REACTORS, OPERATIONS RESEARCH
Scilab software as an alternative low-cost computing in solving the linear equations problem
NASA Astrophysics Data System (ADS)
Agus, Fahrul; Haviluddin
2017-02-01
Numerical computation packages are widely used both in teaching and research. These packages consist of license (proprietary) and open source software (non-proprietary). One of the reasons to use the package is a complexity of mathematics function (i.e., linear problems). Also, number of variables in a linear or non-linear function has been increased. The aim of this paper was to reflect on key aspects related to the method, didactics and creative praxis in the teaching of linear equations in higher education. If implemented, it could be contribute to a better learning in mathematics area (i.e., solving simultaneous linear equations) that essential for future engineers. The focus of this study was to introduce an additional numerical computation package of Scilab as an alternative low-cost computing programming. In this paper, Scilab software was proposed some activities that related to the mathematical models. In this experiment, four numerical methods such as Gaussian Elimination, Gauss-Jordan, Inverse Matrix, and Lower-Upper Decomposition (LU) have been implemented. The results of this study showed that a routine or procedure in numerical methods have been created and explored by using Scilab procedures. Then, the routine of numerical method that could be as a teaching material course has exploited.
NASA Astrophysics Data System (ADS)
Tang, Yao-Zong; Li, Xiao-Lin
2017-03-01
We first give a stabilized improved moving least squares (IMLS) approximation, which has better computational stability and precision than the IMLS approximation. Then, analysis of the improved element-free Galerkin method is provided theoretically for both linear and nonlinear elliptic boundary value problems. Finally, numerical examples are given to verify the theoretical analysis. Project supported by the National Natural Science Foundation of China (Grant No. 11471063), the Chongqing Research Program of Basic Research and Frontier Technology, China (Grant No. cstc2015jcyjBX0083), and the Educational Commission Foundation of Chongqing City, China (Grant No. KJ1600330).
Program Helps Decompose Complicated Design Problems
NASA Technical Reports Server (NTRS)
Rogers, James L., Jr.
1993-01-01
Time saved by intelligent decomposition into smaller, interrelated problems. DeMAID is knowledge-based software system for ordering sequence of modules and identifying possible multilevel structure for design problem. Displays modules in N x N matrix format. Requires investment of time to generate and refine list of modules for input, it saves considerable amount of money and time in total design process, particularly new design problems in which ordering of modules has not been defined. Program also implemented to examine assembly-line process or ordering of tasks and milestones.
Employee assistance program treats personal problems.
Bednarek, R J; Featherston, H J
1984-03-01
Though the concept of employee assistance programs (EAPs) is widely accepted throughout business and industry, few hospitals have established similar channels for dealing with workers whose personal problems cause work-related problems. Among the reasons for the health care profession's lack of involvement in this area are: lack of information about costs and benefits of EAPs; the hospital's multidisciplinary environment in which standards of employee competence and behavior are set by persons from many disciplines; hospital working hours; and health care workers' attitudes about their vulnerability to illness. St. Benedict's Hospital, Ogden, UT, however, has confronted the question of how to demonstrate Christian concern for its employees. St. Benedict's EAP, the Helping Hand, which was created in 1979, combines progressive disciplinary action with the opportunity for early intervention in and treatment of employees' personal problems. When a worker with personal problems is referred to the EAP coordinator, he or she is matched with the appropriate community or hospital resource for treatment. Supervisors are trained to identify employee problems and to focus on employee job performance rather than on attempting to diagnose the problem. St. Benedict's records during the program's first three years illustrate the human benefits as well as the cost savings of an EAP. Of 92 hospital employees who took part in the EAP, 72 improved their situations or resolved their problems. The hospital's turnover rates declined from 36 percent to 20 percent, and approximately $40,800 in turnover and replacement costs were saved.
Interior-Point Methods for Linear Programming: A Review
ERIC Educational Resources Information Center
Singh, J. N.; Singh, D.
2002-01-01
The paper reviews some recent advances in interior-point methods for linear programming and indicates directions in which future progress can be made. Most of the interior-point methods belong to any of three categories: affine-scaling methods, potential reduction methods and central path methods. These methods are discussed together with…
Interior-Point Methods for Linear Programming: A Review
ERIC Educational Resources Information Center
Singh, J. N.; Singh, D.
2002-01-01
The paper reviews some recent advances in interior-point methods for linear programming and indicates directions in which future progress can be made. Most of the interior-point methods belong to any of three categories: affine-scaling methods, potential reduction methods and central path methods. These methods are discussed together with…
A Heuristic Ceiling Point Algorithm for General Integer Linear Programming
1988-11-01
narrowly satisfies the il h constraint: taking a unit step from x toward the ilh constraining hyperplane in a direction parallel to some coordinate...Business, Stanford Univesity , Stanford, Calif., December 1964. Hillier, F., "Efficient Heuristic Procedures for Integer Linear Programming with an Inte- rior
Women in Jail: Problems, Programs and Resources.
ERIC Educational Resources Information Center
Roy, Marjorie Brown
This manual is designed to assist those individuals or groups responsible for developing educational and vocational programs for women in jail. The first section identifies the needs and problems of women in jail, focussing on discrimination against poor women unable to afford bail, the nonviolent nature of women's crimes, and the inequity of jail…
Multigrid approaches to non-linear diffusion problems on unstructured meshes
NASA Technical Reports Server (NTRS)
Mavriplis, Dimitri J.; Bushnell, Dennis M. (Technical Monitor)
2001-01-01
The efficiency of three multigrid methods for solving highly non-linear diffusion problems on two-dimensional unstructured meshes is examined. The three multigrid methods differ mainly in the manner in which the nonlinearities of the governing equations are handled. These comprise a non-linear full approximation storage (FAS) multigrid method which is used to solve the non-linear equations directly, a linear multigrid method which is used to solve the linear system arising from a Newton linearization of the non-linear system, and a hybrid scheme which is based on a non-linear FAS multigrid scheme, but employs a linear solver on each level as a smoother. Results indicate that all methods are equally effective at converging the non-linear residual in a given number of grid sweeps, but that the linear solver is more efficient in cpu time due to the lower cost of linear versus non-linear grid sweeps.
A novel recurrent neural network with finite-time convergence for linear programming.
Liu, Qingshan; Cao, Jinde; Chen, Guanrong
2010-11-01
In this letter, a novel recurrent neural network based on the gradient method is proposed for solving linear programming problems. Finite-time convergence of the proposed neural network is proved by using the Lyapunov method. Compared with the existing neural networks for linear programming, the proposed neural network is globally convergent to exact optimal solutions in finite time, which is remarkable and rare in the literature of neural networks for optimization. Some numerical examples are given to show the effectiveness and excellent performance of the new recurrent neural network.
LFSPMC: Linear feature selection program using the probability of misclassification
NASA Technical Reports Server (NTRS)
Guseman, L. F., Jr.; Marion, B. P.
1975-01-01
The computational procedure and associated computer program for a linear feature selection technique are presented. The technique assumes that: a finite number, m, of classes exists; each class is described by an n-dimensional multivariate normal density function of its measurement vectors; the mean vector and covariance matrix for each density function are known (or can be estimated); and the a priori probability for each class is known. The technique produces a single linear combination of the original measurements which minimizes the one-dimensional probability of misclassification defined by the transformed densities.
Object matching using a locally affine invariant and linear programming techniques.
Li, Hongsheng; Huang, Xiaolei; He, Lei
2013-02-01
In this paper, we introduce a new matching method based on a novel locally affine-invariant geometric constraint and linear programming techniques. To model and solve the matching problem in a linear programming formulation, all geometric constraints should be able to be exactly or approximately reformulated into a linear form. This is a major difficulty for this kind of matching algorithm. We propose a novel locally affine-invariant constraint which can be exactly linearized and requires a lot fewer auxiliary variables than other linear programming-based methods do. The key idea behind it is that each point in the template point set can be exactly represented by an affine combination of its neighboring points, whose weights can be solved easily by least squares. Errors of reconstructing each matched point using such weights are used to penalize the disagreement of geometric relationships between the template points and the matched points. The resulting overall objective function can be solved efficiently by linear programming techniques. Our experimental results on both rigid and nonrigid object matching show the effectiveness of the proposed algorithm.
Fixed Point Problems for Linear Transformations on Pythagorean Triples
ERIC Educational Resources Information Center
Zhan, M.-Q.; Tong, J.-C.; Braza, P.
2006-01-01
In this article, an attempt is made to find all linear transformations that map a standard Pythagorean triple (a Pythagorean triple [x y z][superscript T] with y being even) into a standard Pythagorean triple, which have [3 4 5][superscript T] as their fixed point. All such transformations form a monoid S* under matrix product. It is found that S*…
Fixed Point Problems for Linear Transformations on Pythagorean Triples
ERIC Educational Resources Information Center
Zhan, M.-Q.; Tong, J.-C.; Braza, P.
2006-01-01
In this article, an attempt is made to find all linear transformations that map a standard Pythagorean triple (a Pythagorean triple [x y z][superscript T] with y being even) into a standard Pythagorean triple, which have [3 4 5][superscript T] as their fixed point. All such transformations form a monoid S* under matrix product. It is found that S*…
New algorithms for linear k-matroid intersection and matroid k-parity problems
Barvinok, A.
1994-12-31
We present algorithms for the k-Matroid Intersection Problem and for the Matroid k-Parity Problem when the matroids are represented over the field of rational numbers and k > 2. The computational complexity of the algorithms is linear in the cardinality n and singly exponential in the rank r of the matroids. Thus if n grows faster than a linear function in r (this is the case for most combinatorial applications) then the algorithms are asymptotically faster than exhaustive search and provide the best known worst-case complexity. If r = O(log n) then the algorithms have polynomial-time complexity. As an application, we prove that for any fixed k one can determine in polynomial time whether there exist O(log n) pairwise disjoint edges in a given uniform k-hypergraph on n vertices. Our approach extends known methods of linear algebra developed earlier for the case k = 2. Using the generalized Binet-Cauchy formula and its analogue for the Pfaffian we reduce in O(nr{sup 2k}) time the k-Matroid intersection Problem to computation of the hyperdeterminant of a 2k-dimensional r x ... x r tensor and the Matroid k-Parity Problem to computation of the hyperpfaffian of a 2k-dimensional 2r x ... 2r tensor. We use dynamic programming to compute these invariants of tensors using O(r{sup 2k}4{sup rk}) and O(r{sup 2k+1}4{sup r}) arithmetic operations correspondingly.
An alternative method on quadratic programming problems
NASA Astrophysics Data System (ADS)
Dasril, Y.; Mohd, I. B.; Mustaffa, I.; Aminuddin, MMM.
2015-05-01
In this paper we proposed an alternative approach to find the optimum solution of quadratic programming problems (QPP) in its original form without additional information such as slack variable, surplus variable or artificial variable as done in other favourite methods. This approached is based on the violated constraints by the unconstrained optimum. The optimal solution of QPP obtained by searching from initial point to another point alongside of feasible region.
A linear regression solution to the spatial autocorrelation problem
NASA Astrophysics Data System (ADS)
Griffith, Daniel A.
The Moran Coefficient spatial autocorrelation index can be decomposed into orthogonal map pattern components. This decomposition relates it directly to standard linear regression, in which corresponding eigenvectors can be used as predictors. This paper reports comparative results between these linear regressions and their auto-Gaussian counterparts for the following georeferenced data sets: Columbus (Ohio) crime, Ottawa-Hull median family income, Toronto population density, southwest Ohio unemployment, Syracuse pediatric lead poisoning, and Glasgow standard mortality rates, and a small remotely sensed image of the High Peak district. This methodology is extended to auto-logistic and auto-Poisson situations, with selected data analyses including percentage of urban population across Puerto Rico, and the frequency of SIDs cases across North Carolina. These data analytic results suggest that this approach to georeferenced data analysis offers considerable promise.
The acoustics of a concert hall as a linear problem
NASA Astrophysics Data System (ADS)
Lokki, Tapio; Pätynen, Jukka
2015-01-01
The main purpose of a concert hall is to convey sound from musicians to listeners and to reverberate the music for more pleasant experience in the audience area. This process is linear and can be represented with impulse responses. However, by studying measured and simulated impulse responses for decades, researchers have not been able to exhaustively explain the success and reputation of certain concert halls.
Linear programming model to develop geodiversity map using utility theory
NASA Astrophysics Data System (ADS)
Sepehr, Adel
2015-04-01
In this article, the classification and mapping of geodiversity based on a quantitative methodology was accomplished using linear programming, the central idea of which being that geosites and geomorphosites as main indicators of geodiversity can be evaluated by utility theory. A linear programming method was applied for geodiversity mapping over Khorasan-razavi province located in eastern north of Iran. In this route, the main criteria for distinguishing geodiversity potential in the studied area were considered regarding rocks type (lithology), faults position (tectonic process), karst area (dynamic process), Aeolian landforms frequency and surface river forms. These parameters were investigated by thematic maps including geology, topography and geomorphology at scales 1:100'000, 1:50'000 and 1:250'000 separately, imagery data involving SPOT, ETM+ (Landsat 7) and field operations directly. The geological thematic layer was simplified from the original map using a practical lithologic criterion based on a primary genetic rocks classification representing metamorphic, igneous and sedimentary rocks. The geomorphology map was provided using DEM at scale 30m extracted by ASTER data, geology and google earth images. The geology map shows tectonic status and geomorphology indicated dynamic processes and landform (karst, Aeolian and river). Then, according to the utility theory algorithms, we proposed a linear programming to classify geodiversity degree in the studied area based on geology/morphology parameters. The algorithm used in the methodology was consisted a linear function to be maximized geodiversity to certain constraints in the form of linear equations. The results of this research indicated three classes of geodiversity potential including low, medium and high status. The geodiversity potential shows satisfied conditions in the Karstic areas and Aeolian landscape. Also the utility theory used in the research has been decreased uncertainty of the evaluations.
ERIC Educational Resources Information Center
Matzke, Orville R.
The purpose of this study was to formulate a linear programming model to simulate a foundation type support program and to apply this model to a state support program for the public elementary and secondary school districts in the State of Iowa. The model was successful in producing optimal solutions to five objective functions proposed for…
Mixed-Integer Conic Linear Programming: Challenges and Perspectives
2013-10-01
The novel DCCs for MISOCO may be used in branch- and-cut algorithms when solving MISOCO problems. The experimental software CICLO was developed to...perform limited, but rigorous computational experiments. The CICLO solver utilizes continuous SOCO solvers, MOSEK, CPLES or SeDuMi, builds on the open...submitted Fall 2013. Software: 1. CICLO : Integer conic linear optimization package. Authors: J.C. Góez, T.K. Ralphs, Y. Fu, and T. Terlaky
Algorithmic Trading with Developmental and Linear Genetic Programming
NASA Astrophysics Data System (ADS)
Wilson, Garnett; Banzhaf, Wolfgang
A developmental co-evolutionary genetic programming approach (PAM DGP) and a standard linear genetic programming (LGP) stock trading systemare applied to a number of stocks across market sectors. Both GP techniques were found to be robust to market fluctuations and reactive to opportunities associated with stock price rise and fall, with PAMDGP generating notably greater profit in some stock trend scenarios. Both algorithms were very accurate at buying to achieve profit and selling to protect assets, while exhibiting bothmoderate trading activity and the ability to maximize or minimize investment as appropriate. The content of the trading rules produced by both algorithms are also examined in relation to stock price trend scenarios.
NASA Astrophysics Data System (ADS)
Xu, Jiuping; Li, Jun
2002-09-01
In this paper a class of stochastic multiple-objective programming problems with one quadratic, several linear objective functions and linear constraints has been introduced. The former model is transformed into a deterministic multiple-objective nonlinear programming model by means of the introduction of random variables' expectation. The reference direction approach is used to deal with linear objectives and results in a linear parametric optimization formula with a single linear objective function. This objective function is combined with the quadratic function using the weighted sums. The quadratic problem is transformed into a linear (parametric) complementary problem, the basic formula for the proposed approach. The sufficient and necessary conditions for (properly, weakly) efficient solutions and some construction characteristics of (weakly) efficient solution sets are obtained. An interactive algorithm is proposed based on reference direction and weighted sums. Varying the parameter vector on the right-hand side of the model, the DM can freely search the efficient frontier with the model. An extended portfolio selection model is formed when liquidity is considered as another objective to be optimized besides expectation and risk. The interactive approach is illustrated with a practical example.
Finding Stable Orientations of Assemblies with Linear Programming
1993-06-01
AD-A266 990 Finding Stable Orientations of Assemblies with Linear Programming David Baraff Raju Mattikalli Bruno Repetto Pradeep Khosla CMU-RI-TR-93...Mattikalli, Bruno Repetto and Pradeep Khosla 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER The Robotics... Repetto , and D. Baraff. Stability of assemblies. In Interna- tional Conference on Intelligent Robots and Systems, page (to appear). IEEE/RSJ, July 1993
Method for Solving Physical Problems Described by Linear Differential Equations
NASA Astrophysics Data System (ADS)
Belyaev, B. A.; Tyurnev, V. V.
2017-01-01
A method for solving physical problems is suggested in which the general solution of a differential equation in partial derivatives is written in the form of decomposition in spherical harmonics with indefinite coefficients. Values of these coefficients are determined from a comparison of the decomposition with a solution obtained for any simplest particular case of the examined problem. The efficiency of the method is demonstrated on an example of calculation of electromagnetic fields generated by a current-carrying circular wire. The formulas obtained can be used to analyze paths in the near-field magnetic (magnetically inductive) communication systems working in moderately conductive media, for example, in sea water.
From a Nonlinear, Nonconvex Variational Problem to a Linear, Convex Formulation
Egozcue, J. Meziat, R. Pedregal, P.
2002-12-19
We propose a general approach to deal with nonlinear, nonconvex variational problems based on a reformulation of the problem resulting in an optimization problem with linear cost functional and convex constraints. As a first step we explicitly explore these ideas to some one-dimensional variational problems and obtain specific conclusions of an analytical and numerical nature.
ERIC Educational Resources Information Center
Kar, Tugrul
2016-01-01
This study examined prospective middle school mathematics teachers' problem-posing skills by investigating their ability to associate linear graphs with daily life situations. Prospective teachers were given linear graphs and asked to pose problems that could potentially be represented by the graphs. Their answers were analyzed in two stages. In…
Solving of variational inequalities by reducing to the linear complementarity problem
NASA Astrophysics Data System (ADS)
Gabidullina, Z. R.
2016-11-01
We study the variational inequalities closely connected with the linear separation problem of the convex polyhedrain the Euclidean space. For solving of these inequalities, we apply the reduction to the linear complementarity problem. Such reduction allows one to solve the variational inequalities with the help of the Matlab software package.
Xia, Bisheng; Qian, Xin; Yao, Hong
2017-09-18
Although the risk-explicit interval linear programming (REILP) model has solved the problem of having interval solutions, it has an equity problem, which can lead to unbalanced allocation between different decision variables. Therefore, an improved REILP model is proposed. This model adds an equity objective function and three constraint conditions to overcome this equity problem. In this case, pollution reduction is in proportion to pollutant load, which supports balanced development between different regional economies. The model is used to solve the problem of pollution load allocation in a small transboundary watershed. Compared with the REILP original model result, our model achieves equity between the upstream and downstream pollutant loads; it also overcomes the problem of greatest pollution reduction, where sources are nearest to the control section. The model provides a better solution to the problem of pollution load allocation than previous versions.
Using Parallel Banded Linear System Solvers in Generalized Eigenvalue Problems
1993-09-01
systems. The PPT algorithm is similar to an algorithm introduced by Lawrie and Sameh in [18]. The PDD algorithm is a variant of PPT which uses the fa-t...AND L. JOHNSSON, Solving banded systems on a parallel processor, Parallel Comput., 5 (1987), pp. 219-246. [10] J. J. DONGARRA AND A. SAMEH , On some...symmetric generalized matrix eigenvalur problem, SIAM J. Matrix Anal. Appl., 14 (1993). [18] D. H. LAWRIE AND A. H. SAMEH , The computation and
NASA Technical Reports Server (NTRS)
Banks, H. T.; Silcox, R. J.; Keeling, S. L.; Wang, C.
1989-01-01
A unified treatment of the linear quadratic tracking (LQT) problem, in which a control system's dynamics are modeled by a linear evolution equation with a nonhomogeneous component that is linearly dependent on the control function u, is presented; the treatment proceeds from the theoretical formulation to a numerical approximation framework. Attention is given to two categories of LQT problems in an infinite time interval: the finite energy and the finite average energy. The behavior of the optimal solution for finite time-interval problems as the length of the interval tends to infinity is discussed. Also presented are the formulations and properties of LQT problems in a finite time interval.
NASA Technical Reports Server (NTRS)
Banks, H. T.; Silcox, R. J.; Keeling, S. L.; Wang, C.
1989-01-01
A unified treatment of the linear quadratic tracking (LQT) problem, in which a control system's dynamics are modeled by a linear evolution equation with a nonhomogeneous component that is linearly dependent on the control function u, is presented; the treatment proceeds from the theoretical formulation to a numerical approximation framework. Attention is given to two categories of LQT problems in an infinite time interval: the finite energy and the finite average energy. The behavior of the optimal solution for finite time-interval problems as the length of the interval tends to infinity is discussed. Also presented are the formulations and properties of LQT problems in a finite time interval.
CSOLNP: Numerical Optimization Engine for Solving Non-linearly Constrained Problems.
Zahery, Mahsa; Maes, Hermine H; Neale, Michael C
2017-08-01
We introduce the optimizer CSOLNP, which is a C++ implementation of the R package RSOLNP (Ghalanos & Theussl, 2012, Rsolnp: General non-linear optimization using augmented Lagrange multiplier method. R package version, 1) alongside some improvements. CSOLNP solves non-linearly constrained optimization problems using a Sequential Quadratic Programming (SQP) algorithm. CSOLNP, NPSOL (a very popular implementation of SQP method in FORTRAN (Gill et al., 1986, User's guide for NPSOL (version 4.0): A Fortran package for nonlinear programming (No. SOL-86-2). Stanford, CA: Stanford University Systems Optimization Laboratory), and SLSQP (another SQP implementation available as part of the NLOPT collection (Johnson, 2014, The NLopt nonlinear-optimization package. Retrieved from http://ab-initio.mit.edu/nlopt)) are three optimizers available in OpenMx package. These optimizers are compared in terms of runtimes, final objective values, and memory consumption. A Monte Carlo analysis of the performance of the optimizers was performed on ordinal and continuous models with five variables and one or two factors. While the relative difference between the objective values is less than 0.5%, CSOLNP is in general faster than NPSOL and SLSQP for ordinal analysis. As for continuous data, none of the optimizers performs consistently faster than the others. In terms of memory usage, we used Valgrind's heap profiler tool, called Massif, on one-factor threshold models. CSOLNP and NPSOL consume the same amount of memory, while SLSQP uses 71 MB more memory than the other two optimizers.
Molecular solutions to the binary integer programming problem based on DNA computation.
Yeh, Chung-Wei; Chu, Chih-Ping; Wu, Kee-Rong
2006-01-01
Binary optimization is a widely investigated topic in integer linear programming. This study proposes a DNA-based computing algorithm for solving the significantly large binary integer programming (BIP) problem. The proposed approach is based upon Adleman and Lipton's DNA operations to solve the BIP problem. The potential of DNA computation for the BIP problem is promising given the operational time complexity of O(nxk).
Theoretical and Numerical Analysis for Non-Linear Interface Problems
2007-04-19
Report 17 . LIMITATION OF ABSTRACT SAR 15. NUMBER OF PAGES 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 5c. PROGRAM ELEMENT NUMBER 5b...8217$94ZY.4,;X/,)@4P*<I $AC+4)@4&@C+&[CE*]\\_^ \\_`<ab#^c5J$’&+&+$’*.3%&d4&@(-421$e/’>f$gC+"% 4Ph =42097%&R*,I/,B8CE*.5J/<CE$ Ci/,)@:.42C )@41
Romeijn, H Edwin; Ahuja, Ravindra K; Dempsey, James F; Kumar, Arvind; Li, Jonathan G
2003-11-07
We present a novel linear programming (LP) based approach for efficiently solving the intensity modulated radiation therapy (IMRT) fluence-map optimization (FMO) problem to global optimality. Our model overcomes the apparent limitations of a linear-programming approach by approximating any convex objective function by a piecewise linear convex function. This approach allows us to retain the flexibility offered by general convex objective functions, while allowing us to formulate the FMO problem as a LP problem. In addition, a novel type of partial-volume constraint that bounds the tail averages of the differential dose-volume histograms of structures is imposed while retaining linearity as an alternative approach to improve dose homogeneity in the target volumes, and to attempt to spare as many critical structures as possible. The goal of this work is to develop a very rapid global optimization approach that finds high quality dose distributions. Implementation of this model has demonstrated excellent results. We found globally optimal solutions for eight 7-beam head-and-neck cases in less than 3 min of computational time on a single processor personal computer without the use of partial-volume constraints. Adding such constraints increased the running times by a factor of 2-3, but improved the sparing of critical structures. All cases demonstrated excellent target coverage (> 95%), target homogeneity (< 10% overdosing and < 7% underdosing) and organ sparing using at least one of the two models.
NASA Astrophysics Data System (ADS)
Han, Jeongwoo
Decision-making under uncertainty is particularly challenging in the case of multi-disciplinary, multilevel system optimization problems. Subsystem interactions cause strong couplings, which may be amplified by uncertainty. Thus, effective coordination strategies can be particularly beneficial. Analytical target cascading (ATC) is a deterministic optimization method for multilevel hierarchical systems, which was recently extended to probabilistic design. Solving the optimization problem requires propagation of uncertainty, namely, evaluating or estimating output distributions given random input variables. This uncertainty propagation can be a challenging and computationally expensive task for nonlinear functions, but is relatively easy for linear ones. In order to overcome the difficulty in uncertainty propagation, this dissertation introduces the use of Sequential Linear Programming (SLP) for solving ATC problems, and specifically extends this use for Probabilistic Analytical Target Cascading (PATC) problems. A new coordination strategy is proposed for ATC and PATC, which coordinates linking variables among subproblems using sequential lineralizations. By linearizing and solving a hierarchy of problems successively, the algorithm takes advantage of the simplicity and ease of uncertainty propagation for a linear system. Linearity of subproblems is maintained using an Linfinity norm to measure deviations between targets and responses. A subproblem suspension strategy is used to temporarily suspend inclusion of subproblems that do not need significant redesign, based on trust region and target value step size. A global convergence proof of the SLP-based coordination strategy is derived. Experiments with test problems show that, relative to standard ATC and PATC coordination, the number of subproblem evaluations is reduced considerably while maintaining accuracy. To demonstrate the applicability of the proposed strategies to problems of practical complexity, a hybrid
Usefulness and problems of stereotactic radiosurgery using a linear accelerator.
Naoi, Y; Cho, N; Miyauchi, T; Iizuka, Y; Maehara, T; Katayama, H
1996-01-01
Since the introduction of linac radiosurgery in October 1994, we have treated 27 patients with 36 lesions. We treated nine AVM, 12 metastatic brain tumors, two malignant lymphomas, one anaplastic astrocytoma, two meningiomas, and one brain tumor of unknown pathology. In the follow-up examinations at least five months after treatment, the local control rate was 83% for the metastatic tumors, and two malignant lymphomas disappeared completely. In addition, satisfactory results have been obtained with AVM and other brain tumors without any side effects. In comparison with gamma-knife radiosurgery, linac radiosurgery has some disadvantages such as longer treatment time and cumbersome accuracy control, but if accuracy control is performed periodically, accuracies of 1 mm or less can be obtained. There is some strengths of linac radiosurgery as follow. 1) The acquisition cost is relatively low. 2) Dose distribution are equivalent to gamma-knife. 3) There is no field size limitation. 4) There is great flexibility in beam delivery and linac systems. Radiosurgery using linear accelerators seems to become widely accepted in the future.
NASA Technical Reports Server (NTRS)
Armstrong, E. S.
1975-01-01
A digital computer program (ORACLS) for implementing the optimal regulator theory approach to the design of controllers for linear time-invariant systems is described. The user-oriented program employs the latest numerical techniques and is applicable to both the digital and continuous control problems.
Towards Resolving the Crab Sigma-Problem: A Linear Accelerator?
NASA Technical Reports Server (NTRS)
Contopoulos, Ioannis; Kazanas, Demosthenes; White, Nicholas E. (Technical Monitor)
2002-01-01
Using the exact solution of the axisymmetric pulsar magnetosphere derived in a previous publication and the conservation laws of the associated MHD flow, we show that the Lorentz factor of the outflowing plasma increases linearly with distance from the light cylinder. Therefore, the ratio of the Poynting to particle energy flux, generically referred to as sigma, decreases inversely proportional to distance, from a large value (typically approx. greater than 10(exp 4)) near the light cylinder to sigma approx. = 1 at a transition distance R(sub trans). Beyond this distance the inertial effects of the outflowing plasma become important and the magnetic field geometry must deviate from the almost monopolar form it attains between R(sub lc), and R(sub trans). We anticipate that this is achieved by collimation of the poloidal field lines toward the rotation axis, ensuring that the magnetic field pressure in the equatorial region will fall-off faster than 1/R(sup 2) (R being the cylindrical radius). This leads both to a value sigma = a(sub s) much less than 1 at the nebular reverse shock at distance R(sub s) (R(sub s) much greater than R(sub trans)) and to a component of the flow perpendicular to the equatorial component, as required by observation. The presence of the strong shock at R = R(sub s) allows for the efficient conversion of kinetic energy into radiation. We speculate that the Crab pulsar is unique in requiring sigma(sub s) approx. = 3 x 10(exp -3) because of its small translational velocity, which allowed for the shock distance R(sub s) to grow to values much greater than R(sub trans).
Approximations for generalized bilevel programming problem
Morgan, J.; Lignola, M.B.
1994-12-31
The following mathematical programming with variational inequality constraints, also called {open_quotes}Generalized bilevel programming problem{close_quotes}, is considered: minimize f(x, y) subject to x {element_of} U and y {element_of} S(x) where S(x) is the solution set of a parametrized variational inequality; i.e., S(x) = {l_brace}y {element_of} U(x): F(x, y){sup T} (y-z){<=} 0 {forall}z {element_of} U (x){r_brace} with f : R{sup n} {times} R{sup m} {yields} {bar R}, F : R{sup n} {times} R{sup m} - R{sup n} and U(x) = {l_brace}y {element_of} {Gamma}{sup T} c{sub i} (x, y) {<=} 0 for 1 = 1, p{r_brace} with c : R{sup n} {times} R{sup m} {yields} R and U{sub ad}, {Gamma} be compact subsets of R{sup m} and R{sup n} respectively. Approximations will be presented to guarantee not only existence of solutions but also convergence of them under perturbations of the data. Connections with previous results obtained when the lower level problem is an optimization one, will be given.
Mining Knowledge from Multiple Criteria Linear Programming Models
NASA Astrophysics Data System (ADS)
Zhang, Peng; Zhu, Xingquan; Li, Aihua; Zhang, Lingling; Shi, Yong
As a promising data mining tool, Multiple Criteria Linear Programming (MCLP) has been widely used in business intelligence. However, a possible limitation of MCLP is that it generates unexplainable black-box models which can only tell us results without reasons. To overcome this shortage, in this paper, we propose a Knowledge Mining strategy which mines from black-box MCLP models to get explainable and understandable knowledge. Different from the traditional Data Mining strategy which focuses on mining knowledge from data, this Knowledge Mining strategy provides a new vision of mining knowledge from black-box models, which can be taken as a special topic of “Intelligent Knowledge Management”.
Gene Golub; Kwok Ko
2009-03-30
The solutions of sparse eigenvalue problems and linear systems constitute one of the key computational kernels in the discretization of partial differential equations for the modeling of linear accelerators. The computational challenges faced by existing techniques for solving those sparse eigenvalue problems and linear systems call for continuing research to improve on the algorithms so that ever increasing problem size as required by the physics application can be tackled. Under the support of this award, the filter algorithm for solving large sparse eigenvalue problems was developed at Stanford to address the computational difficulties in the previous methods with the goal to enable accelerator simulations on then the world largest unclassified supercomputer at NERSC for this class of problems. Specifically, a new method, the Hemitian skew-Hemitian splitting method, was proposed and researched as an improved method for solving linear systems with non-Hermitian positive definite and semidefinite matrices.
Global symmetry relations in linear and viscoplastic mobility problems
NASA Astrophysics Data System (ADS)
Kamrin, Ken; Goddard, Joe
2014-11-01
The mobility tensor of a textured surface is a homogenized effective boundary condition that describes the effective slip of a fluid adjacent to the surface in terms of an applied shear traction far above the surface. In the Newtonian fluid case, perturbation analysis yields a mobility tensor formula, which suggests that regardless of the surface texture (i.e. nonuniform hydrophobicity distribution and/or height fluctuations) the mobility tensor is always symmetric. This conjecture is verified using a Lorentz reciprocity argument. It motivates the question of whether such symmetries would arise for nonlinear constitutive relations and boundary conditions, where the mobility tensor is not a constant but a function of the applied stress. We show that in the case of a strongly dissipative nonlinear constitutive relation--one whose strain-rate relates to the stress solely through a scalar Edelen potential--and strongly dissipative surface boundary conditions--one whose hydrophobic character is described by a potential relating slip to traction--the mobility function of the surface also maintains tensorial symmetry. By extension, the same variational arguments can be applied in problems such as the permeability tensor for viscoplastic flow through porous media, and we find that similar symmetries arise. These findings could be used to simplify the characterization of viscoplastic drag in various anisotropic media. (Joe Goddard is a former graduate student of Acrivos).
Solution algorithms for non-linear singularly perturbed optimal control problems
NASA Technical Reports Server (NTRS)
Ardema, M. D.
1983-01-01
The applicability and usefulness of several classical and other methods for solving the two-point boundary-value problem which arises in non-linear singularly perturbed optimal control are assessed. Specific algorithms of the Picard, Newton and averaging types are formally developed for this class of problem. The computational requirements associated with each algorithm are analysed and compared with the computational requirement of the method of matched asymptotic expansions. Approximate solutions to a linear and a non-linear problem are obtained by each method and compared.
Problems and limitations of voluntary cleanup programs
Johnson, S.F.
1995-12-31
At least a dozen states have already implemented voluntary cleanup programs (VCPs). Provisions to promote state VCPs were prominent in the EPA`s 1994 proposed revisions to CERCLA and in current legislative initiatives. Under the VCP, property owners voluntarily enroll to investigate and remediate contaminated sites with the aegis of a state agency and thus avoid involvement with the federal Superfund program. When the state agency is satisfied with the condition of the site, it issues a certificate to the owner. The VCP is meant to mitigate unintended consequences of CERCLA such as the economic abandonment of urban industrial sites in favor of unpolluted suburban sites. The VCP concept has been combined with other reforms including cleanup standards, financial incentives, and independent action. The effectiveness of voluntary cleanup programs is limited by the costs of investigation and cleanup relative to the value of the property in question. It is also limited when property has environmental problems outside the traditional focus of state Superfund agencies on soil and groundwater contamination. VCPs also have potential unintended consequences of their own. The VCP concept is consistent with a 15 year trend of increasing government attention and involvement with sites of diminishing health and environmental significance. VCP may reinforce the perception of liability and unwittingly raise the standard of due diligence in property assessments, especially if combined with generic cleanup standard.
Carey, G.F.; Young, D.M.
1993-12-31
The program outlined here is directed to research on methods, algorithms, and software for distributed parallel supercomputers. Of particular interest are finite element methods and finite difference methods together with sparse iterative solution schemes for scientific and engineering computations of very large-scale systems. Both linear and nonlinear problems will be investigated. In the nonlinear case, applications with bifurcation to multiple solutions will be considered using continuation strategies. The parallelizable numerical methods of particular interest are a family of partitioning schemes embracing domain decomposition, element-by-element strategies, and multi-level techniques. The methods will be further developed incorporating parallel iterative solution algorithms with associated preconditioners in parallel computer software. The schemes will be implemented on distributed memory parallel architectures such as the CRAY MPP, Intel Paragon, the NCUBE3, and the Connection Machine. We will also consider other new architectures such as the Kendall-Square (KSQ) and proposed machines such as the TERA. The applications will focus on large-scale three-dimensional nonlinear flow and reservoir problems with strong convective transport contributions. These are legitimate grand challenge class computational fluid dynamics (CFD) problems of significant practical interest to DOE. The methods developed and algorithms will, however, be of wider interest.
Discrete Time McKean–Vlasov Control Problem: A Dynamic Programming Approach
Pham, Huyên Wei, Xiaoli
2016-12-15
We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean–Vlasov control problem.
Murray, W.; Saunders, M.A.
1990-03-01
During the last twelve months, research has concentrated on barrier- function methods for linear programming (LP) and quadratic programming (QP). Some ground-work for the application of barrier methods to nonlinearly constrained problems has also begun. In our previous progress report we drew attention to the difficulty of developing robust implementations of barrier methods for LP. We have continued to refine both the primal algorithm and the dual algorithm. We still do not claim that the barrier algorithms are as robust as the simplex method; however, the dual algorithm has solved all the problems in our extensive test set. We have also gained some experience with using the algorithms to solve aircrew scheduling problems.
Applying EXCEL Solver to a watershed management goal-programming problem
J. E. de Steiguer
2000-01-01
This article demonstrates the application of EXCELÂ® spreadsheet linear programming (LP) solver to a watershed management multiple use goal programming (GP) problem. The data used to demonstrate the application are from a published study for a watershed in northern Colorado. GP has been used by natural resource managers for many years. However, the GP solution by means...
NASA Astrophysics Data System (ADS)
Kassa, Semu Mitiku; Tsegay, Teklay Hailay
2017-08-01
Tri-level optimization problems are optimization problems with three nested hierarchical structures, where in most cases conflicting objectives are set at each level of hierarchy. Such problems are common in management, engineering designs and in decision making situations in general, and are known to be strongly NP-hard. Existing solution methods lack universality in solving these types of problems. In this paper, we investigate a tri-level programming problem with quadratic fractional objective functions at each of the three levels. A solution algorithm has been proposed by applying fuzzy goal programming approach and by reformulating the fractional constraints to equivalent but non-fractional non-linear constraints. Based on the transformed formulation, an iterative procedure is developed that can yield a satisfactory solution to the tri-level problem. The numerical results on various illustrative examples demonstrated that the proposed algorithm is very much promising and it can also be used to solve larger-sized as well as n-level problems of similar structure.
LCAP2 (Linear Controls Analysis Program). Volume 3. Source Code Description.
1983-11-15
The computer program LCAP2 (Linear Controls Analysis Program) provides the analyst with the capability to numerically perform classical linear ... control analysis techniques such as transfer function manipulation, transfer function evaluation, frequency response, root locus, time response and sampled
LCAP2 (Linear Controls Analysis Program). Volume 2. Interactive LCAP2 User’s Guide.
1983-11-15
The computer program LCAP2 (Linear Controls Analysis Program) provides the analyst with the capability to numerically perform classical linear ... control analysis techniques such as transfer function manuipulation, transfer function evaluation, frequency response, root locus, time response and sampled
LCAP2 (Linear Control Analysis Program). Volume 1. Batch LCAP2 User’s Guide.
1983-11-15
The computer program LCAP2 (Linear Controls Analysis Program) provides the analyst with the capability to numerically perform classical linear ... control analysis techniques such as transfer function manipulation, transfer function evaluation, frequency response, root locus, time response and sampled
Evaluation of linear solvers for oil reservoir simulation problems. Part 2: The fully implicit case
Joubert, W.; Janardhan, R.
1997-12-01
A previous paper [Joubert/Biswas 1997] contained investigations of linear solver performance for matrices arising from Amoco`s Falcon parallel oil reservoir simulation code using the IMPES formulation (implicit pressure, explicit saturation). In this companion paper, similar issues are explored for linear solvers applied to matrices arising from more difficult fully implicit problems. The results of numerical experiments are given.
Bramble, J.H.; Pasciak, J.E.
1981-01-01
The linearized scalar potential formulation of the magnetostatic field problem is considered. The approach involves a reformulation of the continuous problem as a parametric boundary problem. By the introduction of a spherical interface and the use of spherical harmonics, the infinite boundary condition can also be satisfied in the parametric framework. The reformulated problem is discretized by finite element techniques and a discrete parametric problem is solved by conjugate gradient iteration. This approach decouples the problem in that only standard Neumann type elliptic finite element systems on separate bounded domains need be solved. The boundary conditions at infinity and the interface conditions are satisfied during the boundary parametric iteration.
Xu, Andrew Wei
2010-09-01
In genome rearrangement, given a set of genomes G and a distance measure d, the median problem asks for another genome q that minimizes the total distance [Formula: see text]. This is a key problem in genome rearrangement based phylogenetic analysis. Although this problem is known to be NP-hard, we have shown in a previous article, on circular genomes and under the DCJ distance measure, that a family of patterns in the given genomes--represented by adequate subgraphs--allow us to rapidly find exact solutions to the median problem in a decomposition approach. In this article, we extend this result to the case of linear multichromosomal genomes, in order to solve more interesting problems on eukaryotic nuclear genomes. A multi-way capping problem in the linear multichromosomal case imposes an extra computational challenge on top of the difficulty in the circular case, and this difficulty has been underestimated in our previous study and is addressed in this article. We represent the median problem by the capped multiple breakpoint graph, extend the adequate subgraphs into the capped adequate subgraphs, and prove optimality-preserving decomposition theorems, which give us the tools to solve the median problem and the multi-way capping optimization problem together. We also develop an exact algorithm ASMedian-linear, which iteratively detects instances of (capped) adequate subgraphs and decomposes problems into subproblems. Tested on simulated data, ASMedian-linear can rapidly solve most problems with up to several thousand genes, and it also can provide optimal or near-optimal solutions to the median problem under the reversal/HP distance measures. ASMedian-linear is available at http://sites.google.com/site/andrewweixu .
The use of linear programming in optimization of HDR implant dose distributions.
Jozsef, Gabor; Streeter, Oscar E; Astrahan, Melvin A
2003-05-01
The introduction of high dose rate brachytherapy enabled optimization of dose distributions to be used on a routine basis. The objective of optimization is to homogenize the dose distribution within the implant while simultaneously satisfying dose constraints on certain points. This is accomplished by varying the time the source dwells at different locations. As the dose at any point is a linear function of the dwell times, a linear programming approach seems to be a natural choice. The dose constraints are inherently linear inequalities. Homogeneity requirements are linearized by minimizing the maximum deviation of the doses at points inside the implant from a prescribed dose. The revised simplex method was applied for the solution of this linear programming problem. In the homogenization process the possible source locations were chosen as optimization points. To avoid the problem of the singular value of the dose at a source location from the source itself we define the "self-contribution" as the dose at a small distance from the source. The effect of varying this distance is discussed. Test cases were optimized for planar, biplanar and cylindrical implants. A semi-irregular, fan-like implant with diverging needles was also investigated. Mean central dose calculation based on 3D Delaunay-triangulation of the source locations was used to evaluate the dose distributions. The optimization method resulted in homogeneous distributions (for brachytherapy). Additional dose constraints--when applied--were satisfied. The method is flexible enough to include other linear constraints such as the inclusion of the centroids of the Delaunay-triangulation for homogenization, or limiting the maximum allowable dwell time.
NASA Technical Reports Server (NTRS)
Gibson, J. S.; Rosen, I. G.
1986-01-01
An abstract approximation framework is developed for the finite and infinite time horizon discrete-time linear-quadratic regulator problem for systems whose state dynamics are described by a linear semigroup of operators on an infinite dimensional Hilbert space. The schemes included the framework yield finite dimensional approximations to the linear state feedback gains which determine the optimal control law. Convergence arguments are given. Examples involving hereditary and parabolic systems and the vibration of a flexible beam are considered. Spline-based finite element schemes for these classes of problems, together with numerical results, are presented and discussed.
NASA Technical Reports Server (NTRS)
Gibson, J. S.; Rosen, I. G.
1988-01-01
An abstract approximation framework is developed for the finite and infinite time horizon discrete-time linear-quadratic regulator problem for systems whose state dynamics are described by a linear semigroup of operators on an infinite dimensional Hilbert space. The schemes included the framework yield finite dimensional approximations to the linear state feedback gains which determine the optimal control law. Convergence arguments are given. Examples involving hereditary and parabolic systems and the vibration of a flexible beam are considered. Spline-based finite element schemes for these classes of problems, together with numerical results, are presented and discussed.
Microgrid Reliability Modeling and Battery Scheduling Using Stochastic Linear Programming
Cardoso, Goncalo; Stadler, Michael; Siddiqui, Afzal; Marnay, Chris; DeForest, Nicholas; Barbosa-Povoa, Ana; Ferrao, Paulo
2013-05-23
This paper describes the introduction of stochastic linear programming into Operations DER-CAM, a tool used to obtain optimal operating schedules for a given microgrid under local economic and environmental conditions. This application follows previous work on optimal scheduling of a lithium-iron-phosphate battery given the output uncertainty of a 1 MW molten carbonate fuel cell. Both are in the Santa Rita Jail microgrid, located in Dublin, California. This fuel cell has proven unreliable, partially justifying the consideration of storage options. Several stochastic DER-CAM runs are executed to compare different scenarios to values obtained by a deterministic approach. Results indicate that using a stochastic approach provides a conservative yet more lucrative battery schedule. Lower expected energy bills result, given fuel cell outages, in potential savings exceeding 6percent.
Manipulating multiqudit entanglement witnesses by using linear programming
Jafarizadeh, M. A.; Najarbashi, G.; Habibian, H.
2007-05-15
A class of entanglement witnesses (EWs) called reduction-type entanglement witnesses is introduced, which can detect some multipartite entangled states including positive partial transpose ones with Hilbert space of dimension d{sub 1}(multiply-in-circle sign)d{sub 2}(multiply-in-circle sign){center_dot}{center_dot}{center_dot}(multiply-in-circle sign)d{sub n}. In fact the feasible regions of these EWs turn out to be convex polygons and hence the manipulation of them reduces to linear programming which can be solved exactly by using the simplex method. The decomposability and nondecomposability of these EWs are studied and it is shown that it has a close connection with eigenvalues and optimality of EWs. Also using the Jamiolkowski isomorphism, the corresponding possible positive maps, including the generalized reduction maps of Hall [Phys. Rev. A 72, 022311 (2005)] are obtained.
Linear programming phase unwrapping for dual-wavelength digital holography.
Wang, Zhaomin; Jiao, Jiannan; Qu, Weijuan; Yang, Fang; Li, Hongru; Tian, Ailing; Asundi, Anand
2017-01-20
A linear programming phase unwrapping method in dual-wavelength digital holography is proposed and verified experimentally. The proposed method uses the square of height difference as a convergence standard and theoretically gives the boundary condition in a searching process. A simulation was performed by unwrapping step structures at different levels of Gaussian noise. As a result, our method is capable of recovering the discontinuities accurately. It is robust and straightforward. In the experiment, a microelectromechanical systems sample and a cylindrical lens were measured separately. The testing results were in good agreement with true values. Moreover, the proposed method is applicable not only in digital holography but also in other dual-wavelength interferometric techniques.
Manipulating multiqudit entanglement witnesses by using linear programming
NASA Astrophysics Data System (ADS)
Jafarizadeh, M. A.; Najarbashi, G.; Habibian, H.
2007-05-01
A class of entanglement witnesses (EWs) called reduction-type entanglement witnesses is introduced, which can detect some multipartite entangled states including positive partial transpose ones with Hilbert space of dimension d1⊗d2⊗⋯⊗dn . In fact the feasible regions of these EWs turn out to be convex polygons and hence the manipulation of them reduces to linear programming which can be solved exactly by using the simplex method. The decomposability and nondecomposability of these EWs are studied and it is shown that it has a close connection with eigenvalues and optimality of EWs. Also using the Jamiołkowski isomorphism, the corresponding possible positive maps, including the generalized reduction maps of Hall [Phys. Rev. A 72, 022311 (2005)] are obtained.
Djukanovic, M.; Babic, B.; Milosevic, B.; Sobajic, D.J.; Pao, Y.H. |
1996-05-01
In this paper the blending/transloading facilities are modeled using an interactive fuzzy linear programming (FLP), in order to allow the decision-maker to solve the problem of uncertainty of input information within the fuel scheduling optimization. An interactive decision-making process is formulated in which decision-maker can learn to recognize good solutions by considering all possibilities of fuzziness. The application of the fuzzy formulation is accompanied by a careful examination of the definition of fuzziness, appropriateness of the membership function and interpretation of results. The proposed concept provides a decision support system with integration-oriented features, whereby the decision-maker can learn to recognize the relative importance of factors in the specific domain of optimal fuel scheduling (OFS) problem. The formulation of a fuzzy linear programming problem to obtain a reasonable nonfuzzy solution under consideration of the ambiguity of parameters, represented by fuzzy numbers, is introduced. An additional advantage of the FLP formulation is its ability to deal with multi-objective problems.
SLFP: A stochastic linear fractional programming approach for sustainable waste management
Zhu, H.; Huang, G.H.
2011-12-15
Highlights: > A new fractional programming (SLFP) method is developed for waste management. > SLFP can solve ratio optimization problems associated with random inputs. > A case study of waste flow allocation demonstrates its applicability. > SLFP helps compare objectives of two aspects and reflect system efficiency. > This study supports in-depth analysis of tradeoffs among multiple system criteria. - Abstract: A stochastic linear fractional programming (SLFP) approach is developed for supporting sustainable municipal solid waste management under uncertainty. The SLFP method can solve ratio optimization problems associated with random information, where chance-constrained programming is integrated into a linear fractional programming framework. It has advantages in: (1) comparing objectives of two aspects, (2) reflecting system efficiency, (3) dealing with uncertainty expressed as probability distributions, and (4) providing optimal-ratio solutions under different system-reliability conditions. The method is applied to a case study of waste flow allocation within a municipal solid waste (MSW) management system. The obtained solutions are useful for identifying sustainable MSW management schemes with maximized system efficiency under various constraint-violation risks. The results indicate that SLFP can support in-depth analysis of the interrelationships among system efficiency, system cost and system-failure risk.
Illusion of Linearity in Geometry: Effect in Multiple-Choice Problems
ERIC Educational Resources Information Center
Vlahovic-Stetic, Vesna; Pavlin-Bernardic, Nina; Rajter, Miroslav
2010-01-01
The aim of this study was to examine if there is a difference in the performance on non-linear problems regarding age, gender, and solving situation, and whether the multiple-choice answer format influences students' thinking. A total of 112 students, aged 15-16 and 18-19, were asked to solve problems for which solutions based on proportionality…
Illusion of Linearity in Geometry: Effect in Multiple-Choice Problems
ERIC Educational Resources Information Center
Vlahovic-Stetic, Vesna; Pavlin-Bernardic, Nina; Rajter, Miroslav
2010-01-01
The aim of this study was to examine if there is a difference in the performance on non-linear problems regarding age, gender, and solving situation, and whether the multiple-choice answer format influences students' thinking. A total of 112 students, aged 15-16 and 18-19, were asked to solve problems for which solutions based on proportionality…
ERIC Educational Resources Information Center
Acevedo Nistal, Ana; Van Dooren, Wim; Verschaffel, Lieven
2013-01-01
Thirty-six secondary school students aged 14-16 were interviewed while they chose between a table, a graph or a formula to solve three linear function problems. The justifications for their choices were classified as (1) task-related if they explicitly mentioned the to-be-solved problem, (2) subject-related if students mentioned their own…
Yu, Guoshen; Sapiro, Guillermo; Mallat, Stéphane
2012-05-01
A general framework for solving image inverse problems with piecewise linear estimations is introduced in this paper. The approach is based on Gaussian mixture models, which are estimated via a maximum a posteriori expectation-maximization algorithm. A dual mathematical interpretation of the proposed framework with a structured sparse estimation is described, which shows that the resulting piecewise linear estimate stabilizes the estimation when compared with traditional sparse inverse problem techniques. We demonstrate that, in a number of image inverse problems, including interpolation, zooming, and deblurring of narrow kernels, the same simple and computationally efficient algorithm yields results in the same ballpark as that of the state of the art.
On high-continuity transfinite element formulations for linear-nonlinear transient thermal problems
NASA Technical Reports Server (NTRS)
Tamma, Kumar K.; Railkar, Sudhir B.
1987-01-01
This paper describes recent developments in the applicability of a hybrid transfinite element methodology with emphasis on high-continuity formulations for linear/nonlinear transient thermal problems. The proposed concepts furnish accurate temperature distributions and temperature gradients making use of a relatively smaller number of degrees of freedom; and the methodology is applicable to linear/nonlinear thermal problems. Characteristic features of the formulations are described in technical detail as the proposed hybrid approach combines the major advantages and modeling features of high-continuity thermal finite elements in conjunction with transform methods and classical Galerkin schemes. Several numerical test problems are evaluated and the results obtained validate the proposed concepts for linear/nonlinear thermal problems.
Iterative algorithms for a non-linear inverse problem in atmospheric lidar
NASA Astrophysics Data System (ADS)
Denevi, Giulia; Garbarino, Sara; Sorrentino, Alberto
2017-08-01
We consider the inverse problem of retrieving aerosol extinction coefficients from Raman lidar measurements. In this problem the unknown and the data are related through the exponential of a linear operator, the unknown is non-negative and the data follow the Poisson distribution. Standard methods work on the log-transformed data and solve the resulting linear inverse problem, but neglect to take into account the noise statistics. In this study we show that proper modelling of the noise distribution can improve substantially the quality of the reconstructed extinction profiles. To achieve this goal, we consider the non-linear inverse problem with non-negativity constraint, and propose two iterative algorithms derived using the Karush-Kuhn-Tucker conditions. We validate the algorithms with synthetic and experimental data. As expected, the proposed algorithms out-perform standard methods in terms of sensitivity to noise and reliability of the estimated profile.
Research program with no ''measurement problem''
Noyes, H.P.; Gefwert, C.; Manthey, M.J.
1985-07-01
The ''measurement problem'' of contemporary physics is met by recognizing that the physicist participates when constructing and when applying the theory consisting of the formulated formal and measurement criteria (the expressions and rules) providing the necessary conditions which allow him to compute and measure facts, yet retains objectivity by requiring that these criteria, rules and facts be in corroborative equilibrium. We construct the particulate states of quantum physics by a recursive program which incorporates the non-determinism born of communication between asynchronous processes over a shared memory. Their quantum numbers and coupling constants arise from the construction via the unique 4-level combinatorial hierarchy. The construction defines indivisible quantum events with the requisite supraluminal correlations, yet does not allow supraluminal communication. Measurement criteria incorporate c, h-bar, and m/sub p/ or (not ''and'') G. The resulting theory is discrete throughout, contains no infinities, and, as far as we have developed it, is in agreement with quantum mechanical and cosmological fact.
Some comparison of restarted GMRES and QMR for linear and nonlinear problems
Morgan, R.; Joubert, W.
1994-12-31
Comparisons are made between the following methods: QMR including its transpose-free version, restarted GMRES, and a modified restarted GMRES that uses approximate eigenvectors to improve convergence, For some problems, the modified GMRES is competitive with or better than QMR in terms of the number of matrix-vector products. Also, the GMRES methods can be much better when several similar systems of linear equations must be solved, as in the case of nonlinear problems and ODE problems.
Upper error bounds on calculated outputs of interest for linear and nonlinear structural problems
NASA Astrophysics Data System (ADS)
Ladevèze, Pierre
2006-07-01
This Note introduces new strict upper error bounds on outputs of interest for linear as well as time-dependent nonlinear structural problems calculated by the finite element method. Small-displacement problems without softening, such as (visco)plasticity problems, are included through the standard thermodynamics framework involving internal state variables. To cite this article: P. Ladevèze, C. R. Mecanique 334 (2006).
Initial-value problem for a linear ordinary differential equation of noninteger order
Pskhu, Arsen V
2011-04-30
An initial-value problem for a linear ordinary differential equation of noninteger order with Riemann-Liouville derivatives is stated and solved. The initial conditions of the problem ensure that (by contrast with the Cauchy problem) it is uniquely solvable for an arbitrary set of parameters specifying the orders of the derivatives involved in the equation; these conditions are necessary for the equation under consideration. The problem is reduced to an integral equation; an explicit representation of the solution in terms of the Wright function is constructed. As a consequence of these results, necessary and sufficient conditions for the solvability of the Cauchy problem are obtained. Bibliography: 7 titles.
Program for the solution of multipoint boundary value problems of quasilinear differential equations
NASA Technical Reports Server (NTRS)
1973-01-01
Linear equations are solved by a method of superposition of solutions of a sequence of initial value problems. For nonlinear equations and/or boundary conditions, the solution is iterative and in each iteration a problem like the linear case is solved. A simple Taylor series expansion is used for the linearization of both nonlinear equations and nonlinear boundary conditions. The perturbation method of solution is used in preference to quasilinearization because of programming ease, and smaller storage requirements; and experiments indicate that the desired convergence properties exist although no proof or convergence is given.
Correlates of Problem-Solving in Programming.
ERIC Educational Resources Information Center
Chung, Choi-man
1988-01-01
Examines some correlates of programing ability that can predict the computer programing performance of students. Finds that students who score high on mathematics and spatial tests will score high on programing ability tests. Finds that boys perform significantly better than girls in programing ability, as do those who possess home computers. (KO)
Bhadra, Sahely; Bhattacharyya, Chiranjib; Chandra, Nagasuma R; Mian, I Saira
2009-01-01
Background A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In
Solution of Mixed-Integer Programming Problems on the XT5
Hartman-Baker, Rebecca J; Busch, Ingrid Karin; Hilliard, Michael R; Middleton, Richard S; Schultze, Michael
2009-01-01
In this paper, we describe our experience with solving difficult mixed-integer linear programming problems (MILPs) on the petaflop Cray XT5 system at the National Center for Computational Sciences at Oak Ridge National Laboratory. We describe the algorithmic, software, and hardware needs for solving MILPs and present the results of using PICO, an open-source, parallel, mixed-integer linear programming solver developed at Sandia National Laboratories, to solve canonical MILPs as well as problems of interest arising from the logistics and supply chain management field.
Liang, X B; Si, J
2001-01-01
This paper investigates the existence, uniqueness, and global exponential stability (GES) of the equilibrium point for a large class of neural networks with globally Lipschitz continuous activations including the widely used sigmoidal activations and the piecewise linear activations. The provided sufficient condition for GES is mild and some conditions easily examined in practice are also presented. The GES of neural networks in the case of locally Lipschitz continuous activations is also obtained under an appropriate condition. The analysis results given in the paper extend substantially the existing relevant stability results in the literature, and therefore expand significantly the application range of neural networks in solving optimization problems. As a demonstration, we apply the obtained analysis results to the design of a recurrent neural network (RNN) for solving the linear variational inequality problem (VIP) defined on any nonempty and closed box set, which includes the box constrained quadratic programming and the linear complementarity problem as the special cases. It can be inferred that the linear VIP has a unique solution for the class of Lyapunov diagonally stable matrices, and that the synthesized RNN is globally exponentially convergent to the unique solution. Some illustrative simulation examples are also given.
Future Problem Solving--One Program Meeting Many Needs.
ERIC Educational Resources Information Center
Hume, Katherine C.
2002-01-01
This article describes the Future Problem Solving Program, a year-long curriculum project with competitive and non-competitive options. The international program involves 250,000 students and is designed to help students enlarge, enrich, and make more accurate their images of the future. Team problem solving and individual problem solving…
NASA Astrophysics Data System (ADS)
Abramov, A. A.; Yukhno, L. F.
2017-08-01
Numerical methods are proposed for solving some problems for a system of linear ordinary differential equations in which the basic conditions (which are generally nonlocal ones specified by a Stieltjes integral) are supplemented with redundant (possibly nonlocal) conditions. The system of equations is considered on a finite or infinite interval. The problem of solving the inhomogeneous system of equations and a nonlinear eigenvalue problem are considered. Additionally, the special case of a self-adjoint eigenvalue problem for a Hamiltonian system is addressed. In the general case, these problems have no solutions. A principle for constructing an auxiliary system that replaces the original one and is normally consistent with all specified conditions is proposed. For each problem, a numerical method for solving the corresponding auxiliary problem is described. The method is numerically stable if so is the constructed auxiliary problem.
K-Minimax Stochastic Programming Problems
NASA Astrophysics Data System (ADS)
Nedeva, C.
2007-10-01
The purpose of this paper is a discussion of a numerical procedure based on the simplex method for stochastic optimization problems with partially known distribution functions. The convergence of this procedure is proved by the condition on dual problems.
Solving Fractional Programming Problems based on Swarm Intelligence
NASA Astrophysics Data System (ADS)
Raouf, Osama Abdel; Hezam, Ibrahim M.
2014-04-01
This paper presents a new approach to solve Fractional Programming Problems (FPPs) based on two different Swarm Intelligence (SI) algorithms. The two algorithms are: Particle Swarm Optimization, and Firefly Algorithm. The two algorithms are tested using several FPP benchmark examples and two selected industrial applications. The test aims to prove the capability of the SI algorithms to solve any type of FPPs. The solution results employing the SI algorithms are compared with a number of exact and metaheuristic solution methods used for handling FPPs. Swarm Intelligence can be denoted as an effective technique for solving linear or nonlinear, non-differentiable fractional objective functions. Problems with an optimal solution at a finite point and an unbounded constraint set, can be solved using the proposed approach. Numerical examples are given to show the feasibility, effectiveness, and robustness of the proposed algorithm. The results obtained using the two SI algorithms revealed the superiority of the proposed technique among others in computational time. A better accuracy was remarkably observed in the solution results of the industrial application problems.
Evaluating the impact of AND/OR search on 0-1 integer linear programming.
Marinescu, R; Dechter, R
2010-01-01
AND/OR search spaces accommodate advanced algorithmic schemes for graphical models which can exploit the structure of the model. We extend and evaluate the depth-first and best-first AND/OR search algorithms to solving 0-1 Integer Linear Programs (0-1 ILP) within this framework. We also include a class of dynamic variable ordering heuristics while exploring an AND/OR search tree for 0-1 ILPs. We demonstrate the effectiveness of these search algorithms on a variety of benchmarks, including real-world combinatorial auctions, random uncapacitated warehouse location problems and MAX-SAT instances.
Evaluating the impact of AND/OR search on 0-1 integer linear programming
Dechter, R.
2010-01-01
AND/OR search spaces accommodate advanced algorithmic schemes for graphical models which can exploit the structure of the model. We extend and evaluate the depth-first and best-first AND/OR search algorithms to solving 0-1 Integer Linear Programs (0-1 ILP) within this framework. We also include a class of dynamic variable ordering heuristics while exploring an AND/OR search tree for 0-1 ILPs. We demonstrate the effectiveness of these search algorithms on a variety of benchmarks, including real-world combinatorial auctions, random uncapacitated warehouse location problems and MAX-SAT instances. PMID:21052484
Dufour, F.; Prieto-Rumeau, T.
2016-08-15
We consider a discrete-time constrained discounted Markov decision process (MDP) with Borel state and action spaces, compact action sets, and lower semi-continuous cost functions. We introduce a set of hypotheses related to a positive weight function which allow us to consider cost functions that might not be bounded below by a constant, and which imply the solvability of the linear programming formulation of the constrained MDP. In particular, we establish the existence of a constrained optimal stationary policy. Our results are illustrated with an application to a fishery management problem.
Zheng, Yuanjie; Hunter, Allan A; Wu, Jue; Wang, Hongzhi; Gao, Jianbin; Maguire, Maureen G; Gee, James C
2011-01-01
In this paper, we address the problem of landmark matching based retinal image registration. Two major contributions render our registration algorithm distinguished from many previous methods. One is a novel landmark-matching formulation which enables not only a joint estimation of the correspondences and transformation model but also the optimization with linear programming. The other contribution lies in the introduction of a reinforced self-similarities descriptor in characterizing the local appearance of landmarks. Theoretical analysis and a series of preliminary experimental results show both the effectiveness of our optimization scheme and the high differentiating ability of our features.
Cichocki, A; Unbehauen, R
1994-01-01
In this paper a new class of simplified low-cost analog artificial neural networks with on chip adaptive learning algorithms are proposed for solving linear systems of algebraic equations in real time. The proposed learning algorithms for linear least squares (LS), total least squares (TLS) and data least squares (DLS) problems can be considered as modifications and extensions of well known algorithms: the row-action projection-Kaczmarz algorithm and/or the LMS (Adaline) Widrow-Hoff algorithms. The algorithms can be applied to any problem which can be formulated as a linear regression problem. The correctness and high performance of the proposed neural networks are illustrated by extensive computer simulation results.
ERIC Educational Resources Information Center
Shure, Myrna B.
Designed for teachers of intermediate elementary grades to enable children to learn how to solve the problems they have with others, the underlying goal of the program is to help children develop problem-solving skills so that they learn how to think, not what to think. The interpersonal cognitive problem-solving (ICPS) program includes both…
Multi-point transmission problems for Sturm-Liouville equation with an abstract linear operator
NASA Astrophysics Data System (ADS)
Muhtarov, Fahreddin; Kandemir, Mustafa; Mukhtarov, O. Sh.
2017-04-01
In this paper, we consider the spectral problem for the equation -u″(x) + (A + λI)u(x) = f(x) on the two disjoint intervals (-1, 0) and (0, 1) together with multi-point boundary conditions and supplementary transmission conditions at the point of interaction x = 0, where A is an abstract linear operator. So, our problem is not a pure differential boundary-value one. Starting with the analysis of the principal part of the problem, the coercive estimates, the Fredholmness and isomorphism are established for the main problem. The obtained results are new even in the case of boundary conditions without internal points.
Multigrid for the Galerkin least squares method in linear elasticity: The pure displacement problem
Yoo, Jaechil
1996-12-31
Franca and Stenberg developed several Galerkin least squares methods for the solution of the problem of linear elasticity. That work concerned itself only with the error estimates of the method. It did not address the related problem of finding effective methods for the solution of the associated linear systems. In this work, we prove the convergence of a multigrid (W-cycle) method. This multigrid is robust in that the convergence is uniform as the parameter, v, goes to 1/2 Computational experiments are included.
On Development of a Problem Based Learning System for Linear Algebra with Simple Input Method
NASA Astrophysics Data System (ADS)
Yokota, Hisashi
2011-08-01
Learning how to express a matrix using a keyboard inputs requires a lot of time for most of college students. Therefore, for a problem based learning system for linear algebra to be accessible for college students, it is inevitable to develop a simple method for expressing matrices. Studying the two most widely used input methods for expressing matrices, a simpler input method for expressing matrices is obtained. Furthermore, using this input method and educator's knowledge structure as a concept map, a problem based learning system for linear algebra which is capable of assessing students' knowledge structure and skill is developed.
Lefkoff, L.J.; Gorelick, S.M.
1987-01-01
A FORTRAN-77 computer program code that helps solve a variety of aquifer management problems involving the control of groundwater hydraulics. It is intended for use with any standard mathematical programming package that uses Mathematical Programming System input format. The computer program creates the input files to be used by the optimization program. These files contain all the hydrologic information and management objectives needed to solve the management problem. Used in conjunction with a mathematical programming code, the computer program identifies the pumping or recharge strategy that achieves a user 's management objective while maintaining groundwater hydraulic conditions within desired limits. The objective may be linear or quadratic, and may involve the minimization of pumping and recharge rates or of variable pumping costs. The problem may contain constraints on groundwater heads, gradients, and velocities for a complex, transient hydrologic system. Linear superposition of solutions to the transient, two-dimensional groundwater flow equation is used by the computer program in conjunction with the response matrix optimization method. A unit stress is applied at each decision well and transient responses at all control locations are computed using a modified version of the U.S. Geological Survey two dimensional aquifer simulation model. The program also computes discounted cost coefficients for the objective function and accounts for transient aquifer conditions. (Author 's abstract)
Modified Cholesky factorizations in interior-point algorithms for linear programming.
Wright, S.; Mathematics and Computer Science
1999-01-01
We investigate a modified Cholesky algorithm typical of those used in most interior-point codes for linear programming. Cholesky-based interior-point codes are popular for three reasons: their implementation requires only minimal changes to standard sparse Cholesky algorithms (allowing us to take full advantage of software written by specialists in that area); they tend to be more efficient than competing approaches that use alternative factorizations; and they perform robustly on most practical problems, yielding good interior-point steps even when the coefficient matrix of the main linear system to be solved for the step components is ill conditioned. We investigate this surprisingly robust performance by using analytical tools from matrix perturbation theory and error analysis, illustrating our results with computational experiments. Finally, we point out the potential limitations of this approach.
Very Low-Cost Nutritious Diet Plans Designed by Linear Programming.
ERIC Educational Resources Information Center
Foytik, Jerry
1981-01-01
Provides procedural details of Linear Programing, developed by the U.S. Department of Agriculture to devise a dietary guide for consumers that minimizes food costs without sacrificing nutritional quality. Compares Linear Programming with the Thrifty Food Plan, which has been a basis for allocating coupons under the Food Stamp Program. (CS)
A quadratic-tensor model algorithm for nonlinear least-squares problems with linear constraints
NASA Technical Reports Server (NTRS)
Hanson, R. J.; Krogh, Fred T.
1992-01-01
A new algorithm for solving nonlinear least-squares and nonlinear equation problems is proposed which is based on approximating the nonlinear functions using the quadratic-tensor model by Schnabel and Frank. The algorithm uses a trust region defined by a box containing the current values of the unknowns. The algorithm is found to be effective for problems with linear constraints and dense Jacobian matrices.
A quadratic-tensor model algorithm for nonlinear least-squares problems with linear constraints
NASA Technical Reports Server (NTRS)
Hanson, R. J.; Krogh, Fred T.
1992-01-01
A new algorithm for solving nonlinear least-squares and nonlinear equation problems is proposed which is based on approximating the nonlinear functions using the quadratic-tensor model by Schnabel and Frank. The algorithm uses a trust region defined by a box containing the current values of the unknowns. The algorithm is found to be effective for problems with linear constraints and dense Jacobian matrices.
METLIN-PC: An applications-program package for problems of mathematical programming
Pshenichnyi, B.N.; Sobolenko, L.A.; Sosnovskii, A.A.; Aleksandrova, V.M.; Shul`zhenko, Yu.V.
1994-05-01
The METLIN-PC applications-program package (APP) was developed at the V.M. Glushkov Institute of Cybernetics of the Academy of Sciences of Ukraine on IBM PC XT and AT computers. The present version of the package was written in Turbo Pascal and Fortran-77. The METLIN-PC is chiefly designed for the solution of smooth problems of mathematical programming and is a further development of the METLIN prototype, which was created earlier on a BESM-6 computer. The principal property of the previous package is retained - the applications modules employ a single approach based on the linearization method of B.N. Pschenichnyi. Hence the name {open_quotes}METLIN.{close_quotes}
Preschool-Based Programs for Externalizing Problems
ERIC Educational Resources Information Center
Arnold, David H.; Brown, Sharice A.; Meagher, Susan; Baker, Courtney N.; Dobbs, Jennifer; Doctoroff, Greta L.
2006-01-01
Few mental health initiatives for young children have used classroom programs. Preschool-based efforts targeting externalizing behavior could help prevent conduct disorders. Additional benefits may include improved academic achievement and reduced risk for other mental health difficulties. Pro-grams that target multiple developmental domains are…
Problems and Issues Across Institutions and Programs
Douglas Powell; Jim Wood
2006-01-01
The symposium identified the major barriers to collaboration among institutions and programs. This synthesis, while admittedly drawing from only a sample of the papers presented, provides a synoptic view of the major recurring themes voiced by participants.Several overarching statements were voiced. No one institution or one program in isolation can...
Bilingual Program Management: A Problem Solving Approach.
ERIC Educational Resources Information Center
De George, George P., Ed.
A collection of essays on the management of bilingual education programs is organized in three units: managing in a culturally diverse setting, balancing critical interactions, and special issues. The following papers are included: "Recruiting and Retaining Competent Personnel for Bilingual Education Programs" (Joan E. Friedenberg, Curtis H.…
Preschool-Based Programs for Externalizing Problems
ERIC Educational Resources Information Center
Arnold, David H.; Brown, Sharice A.; Meagher, Susan; Baker, Courtney N.; Dobbs, Jennifer; Doctoroff, Greta L.
2006-01-01
Few mental health initiatives for young children have used classroom programs. Preschool-based efforts targeting externalizing behavior could help prevent conduct disorders. Additional benefits may include improved academic achievement and reduced risk for other mental health difficulties. Pro-grams that target multiple developmental domains are…
NASA Technical Reports Server (NTRS)
Pilkey, W. D.; Chen, Y. H.
1974-01-01
An indirect synthesis method is used in the efficient optimal design of multi-degree of freedom, multi-design element, nonlinear, transient systems. A limiting performance analysis which requires linear programming for a kinematically linear system is presented. The system is selected using system identification methods such that the designed system responds as closely as possible to the limiting performance. The efficiency is a result of the method avoiding the repetitive systems analyses accompanying other numerical optimization methods.
A systematic linear space approach to solving partially described inverse eigenvalue problems
NASA Astrophysics Data System (ADS)
Hu, Sau-Lon James; Li, Haujun
2008-06-01
Most applications of the inverse eigenvalue problem (IEP), which concerns the reconstruction of a matrix from prescribed spectral data, are associated with special classes of structured matrices. Solving the IEP requires one to satisfy both the spectral constraint and the structural constraint. If the spectral constraint consists of only one or few prescribed eigenpairs, this kind of inverse problem has been referred to as the partially described inverse eigenvalue problem (PDIEP). This paper develops an efficient, general and systematic approach to solve the PDIEP. Basically, the approach, applicable to various structured matrices, converts the PDIEP into an ordinary inverse problem that is formulated as a set of simultaneous linear equations. While solving simultaneous linear equations for model parameters, the singular value decomposition method is applied. Because of the conversion to an ordinary inverse problem, other constraints associated with the model parameters can be easily incorporated into the solution procedure. The detailed derivation and numerical examples to implement the newly developed approach to symmetric Toeplitz and quadratic pencil (including mass, damping and stiffness matrices of a linear dynamic system) PDIEPs are presented. Excellent numerical results for both kinds of problem are achieved under the situations that have either unique or infinitely many solutions.
A Longitudinal Solution to the Problem of Differential Linear Growth Patterns in Quasi-Experiments.
ERIC Educational Resources Information Center
Olejnik, Stephen; Porter, Andrew C.
Differential achievement growth patterns between comparison groups is a problem associated with data analysis in compensatory education programs. Children in greatest need of additional assistance, are usually assigned to the program rather than to an alternative treatment so that the comparison groups may vary in several ways, in addition to the…
NASA Technical Reports Server (NTRS)
Bauld, N. R., Jr.; Goree, J. G.
1983-01-01
The accuracy of the finite difference method in the solution of linear elasticity problems that involve either a stress discontinuity or a stress singularity is considered. Solutions to three elasticity problems are discussed in detail: a semi-infinite plane subjected to a uniform load over a portion of its boundary; a bimetallic plate under uniform tensile stress; and a long, midplane symmetric, fiber reinforced laminate subjected to uniform axial strain. Finite difference solutions to the three problems are compared with finite element solutions to corresponding problems. For the first problem a comparison with the exact solution is also made. The finite difference formulations for the three problems are based on second order finite difference formulas that provide for variable spacings in two perpendicular directions. Forward and backward difference formulas are used near boundaries where their use eliminates the need for fictitious grid points.
Analysis of junior high school students' attempt to solve a linear inequality problem
NASA Astrophysics Data System (ADS)
Taqiyuddin, Muhammad; Sumiaty, Encum; Jupri, Al
2017-08-01
Linear inequality is one of fundamental subjects within junior high school mathematics curricula. Several studies have been conducted to asses students' perform on linear inequality. However, it can hardly be found that linear inequality problems are in the form of "ax + b < dx + e" with "a, d ≠ 0", and "a ≠ d" as it can be seen on the textbook used by Indonesian students and several studies. This condition leads to the research questions concerning students' attempt on solving a simple linear inequality problem in this form. In order to do so, the written test was administered to 58 students from two schools in Bandung followed by interviews. The other sources of the data are from teachers' interview and mathematics books used by students. After that, the constant comparative method was used to analyse the data. The result shows that the majority approached the question by doing algebraic operations. Interestingly, most of them did it incorrectly. In contrast, algebraic operations were correctly used by some of them. Moreover, the others performed expected-numbers solution, rewriting the question, translating the inequality into words, and blank answer. Furthermore, we found that there is no one who was conscious of the existence of all-numbers solution. It was found that this condition is reasonably due to how little the learning components concern about why a procedure of solving a linear inequality works and possibilities of linear inequality solution.
Optimal Design of IIR Filters Using Linear Semi-Infinite Programming Method
NASA Astrophysics Data System (ADS)
Yamazaki, Takayuki; Suyama, Kenji
In this paper, an optimal design method for stable IIR(Infinite Impulse Response) filters in a criterion of min-max sense is proposed. The design problem is considered one of the complex Chebyshev approximation for rational function including the stability constraint, we formulated such the problem as a real linear semi-infinite programming using the real rotation theorem. Then, the problem is solved by the three phase method that is one of the methods solving semi-infinite programming problem. The three phase method is composed of three operations. In the first operation, some candidates of active constraints are selected by the iterative simplex method. Next, the second operation integrates some degenerate constraints. In the third operation, the approximation solution obtained until second operation is adjusted so as to satisfy the optimality condition. As a result, the filters designed by the method are more precise than one designed by conventional method. Several design examples are shown to present effectiveness of the proposed method.
Automatic tracking of linear features on SPOT images using dynamic programming
NASA Astrophysics Data System (ADS)
Bonnefon, Regis; Dherete, Pierre; Desachy, Jacky
1999-12-01
Detection of geographic elements on images is important in the perspective of adding new elements in geographic databases which are sometimes old and so, some elements are not represented. Our goal is to look for linear features like roads, rivers or railways on SPOT images with a resolution of 10 meters. Several methods allow this detection to be realized and may be classified in three categories: (1) Detection operators: the best known is the DUDA Road Operator which determine the belonging degree of a pixel to a linear feature from several 5 X 5 filters. Results are often unsatisfactory. It exists too the Infinite Size Exponential Filter (ISEF), which is a derivative filter and allows edge, valley or roof profile to be found on the image. It can be utilized as an additional information for others methods. (2) Structural tracking: from a starting point, an analysis in several directions is performed to determine the best next point (features may be: homogeneity of radiometry, contrast with environment, ...). From this new point and with an updated direction, the process goes on. Difficulty of these methods is the consideration of occlusions (bridges, tunnels, dense vegetation, ...). (3) Dynamic programming: F* algorithm and snakes are the best known. They allow a path with a minimal cost to be found in a search window. Occlusions are not a problem but two points or more near the searched linear feature must be known to define the window. The method described below is a mixture of structural tracking and dynamic programming (F* algorithm).
Development and validation of a general purpose linearization program for rigid aircraft models
NASA Technical Reports Server (NTRS)
Duke, E. L.; Antoniewicz, R. F.
1985-01-01
A FORTRAN program that provides the user with a powerful and flexible tool for the linearization of aircraft models is discussed. The program LINEAR numerically determines a linear systems model using nonlinear equations of motion and a user-supplied, nonlinear aerodynamic model. The system model determined by LINEAR consists of matrices for both the state and observation equations. The program has been designed to allow easy selection and definition of the state, control, and observation variables to be used in a particular model. Also, included in the report is a comparison of linear and nonlinear models for a high performance aircraft.
High Order Finite Difference Methods, Multidimensional Linear Problems and Curvilinear Coordinates
NASA Technical Reports Server (NTRS)
Nordstrom, Jan; Carpenter, Mark H.
1999-01-01
Boundary and interface conditions are derived for high order finite difference methods applied to multidimensional linear problems in curvilinear coordinates. The boundary and interface conditions lead to conservative schemes and strict and strong stability provided that certain metric conditions are met.
Linear Integro-differential Schroedinger and Plate Problems Without Initial Conditions
Lorenzi, Alfredo
2013-06-15
Via Carleman's estimates we prove uniqueness and continuous dependence results for the temporal traces of solutions to overdetermined linear ill-posed problems related to Schroedinger and plate equation. The overdetermination is prescribed in an open subset of the (space-time) lateral boundary.
A Self-Adaptive Projection and Contraction Method for Linear Complementarity Problems
Liao Lizhi Wang Shengli
2003-10-15
In this paper we develop a self-adaptive projection and contraction method for the linear complementarity problem (LCP). This method improves the practical performance of the modified projection and contraction method by adopting a self-adaptive technique. The global convergence of our new method is proved under mild assumptions. Our numerical tests clearly demonstrate the necessity and effectiveness of our proposed method.
Warid, Warid; Hizam, Hashim; Mariun, Norman; Abdul-Wahab, Noor Izzri
2016-01-01
This paper proposes a new formulation for the multi-objective optimal power flow (MOOPF) problem for meshed power networks considering distributed generation. An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. A variant combination of objectives is considered for simultaneous optimization, including power loss, voltage stability, and shunt capacitors MVAR reserve. Fuzzy membership functions for these objectives are designed with extreme targets, whereas the inequality constraints are treated as hard constraints. The multi-objective fuzzy optimal power flow (OPF) formulation was converted into a crisp OPF in a successive linear programming (SLP) framework and solved using an efficient interior point method (IPM). To test the efficacy of the proposed approach, simulations are performed on the IEEE 30-busand IEEE 118-bus test systems. The MFLP optimization is solved for several optimization cases. The obtained results are compared with those presented in the literature. A unique solution with a high satisfaction for the assigned targets is gained. Results demonstrate the effectiveness of the proposed MFLP technique in terms of solution optimality and rapid convergence. Moreover, the results indicate that using the optimal DG location with the MFLP algorithm provides the solution with the highest quality.
Warid, Warid; Hizam, Hashim; Mariun, Norman; Abdul-Wahab, Noor Izzri
2016-01-01
This paper proposes a new formulation for the multi-objective optimal power flow (MOOPF) problem for meshed power networks considering distributed generation. An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. A variant combination of objectives is considered for simultaneous optimization, including power loss, voltage stability, and shunt capacitors MVAR reserve. Fuzzy membership functions for these objectives are designed with extreme targets, whereas the inequality constraints are treated as hard constraints. The multi-objective fuzzy optimal power flow (OPF) formulation was converted into a crisp OPF in a successive linear programming (SLP) framework and solved using an efficient interior point method (IPM). To test the efficacy of the proposed approach, simulations are performed on the IEEE 30-busand IEEE 118-bus test systems. The MFLP optimization is solved for several optimization cases. The obtained results are compared with those presented in the literature. A unique solution with a high satisfaction for the assigned targets is gained. Results demonstrate the effectiveness of the proposed MFLP technique in terms of solution optimality and rapid convergence. Moreover, the results indicate that using the optimal DG location with the MFLP algorithm provides the solution with the highest quality. PMID:26954783
A high-performance feedback neural network for solving convex nonlinear programming problems.
Leung, Yee; Chen, Kai-Zhou; Gao, Xing-Bao
2003-01-01
Based on a new idea of successive approximation, this paper proposes a high-performance feedback neural network model for solving convex nonlinear programming problems. Differing from existing neural network optimization models, no dual variables, penalty parameters, or Lagrange multipliers are involved in the proposed network. It has the least number of state variables and is very simple in structure. In particular, the proposed network has better asymptotic stability. For an arbitrarily given initial point, the trajectory of the network converges to an optimal solution of the convex nonlinear programming problem under no more than the standard assumptions. In addition, the network can also solve linear programming and convex quadratic programming problems, and the new idea of a feedback network may be used to solve other optimization problems. Feasibility and efficiency are also substantiated by simulation examples.
New computer program solves wide variety of heat flow problems
NASA Technical Reports Server (NTRS)
Almond, J. C.
1966-01-01
Boeing Engineering Thermal Analyzer /BETA/ computer program uses numerical methods to provide accurate heat transfer solutions to a wide variety of heat flow problems. The program solves steady-state and transient problems in almost any situation that can be represented by a resistance-capacitance network.
Impulsive Control for Continuous-Time Markov Decision Processes: A Linear Programming Approach
Dufour, F.; Piunovskiy, A. B.
2016-08-15
In this paper, we investigate an optimization problem for continuous-time Markov decision processes with both impulsive and continuous controls. We consider the so-called constrained problem where the objective of the controller is to minimize a total expected discounted optimality criterion associated with a cost rate function while keeping other performance criteria of the same form, but associated with different cost rate functions, below some given bounds. Our model allows multiple impulses at the same time moment. The main objective of this work is to study the associated linear program defined on a space of measures including the occupation measures of the controlled process and to provide sufficient conditions to ensure the existence of an optimal control.
Decomposition and (importance) sampling techniques for multi-stage stochastic linear programs
Infanger, G.
1993-11-01
The difficulty of solving large-scale multi-stage stochastic linear programs arises from the sheer number of scenarios associated with numerous stochastic parameters. The number of scenarios grows exponentially with the number of stages and problems get easily out of hand even for very moderate numbers of stochastic parameters per stage. Our method combines dual (Benders) decomposition with Monte Carlo sampling techniques. We employ importance sampling to efficiently obtain accurate estimates of both expected future costs and gradients and right-hand sides of cuts. The method enables us to solve practical large-scale problems with many stages and numerous stochastic parameters per stage. We discuss the theory of sharing and adjusting cuts between different scenarios in a stage. We derive probabilistic lower and upper bounds, where we use importance path sampling for the upper bound estimation. Initial numerical results turned out to be promising.
Improve Problem Solving Skills through Adapting Programming Tools
NASA Technical Reports Server (NTRS)
Shaykhian, Linda H.; Shaykhian, Gholam Ali
2007-01-01
There are numerous ways for engineers and students to become better problem-solvers. The use of command line and visual programming tools can help to model a problem and formulate a solution through visualization. The analysis of problem attributes and constraints provide insight into the scope and complexity of the problem. The visualization aspect of the problem-solving approach tends to make students and engineers more systematic in their thought process and help them catch errors before proceeding too far in the wrong direction. The problem-solver identifies and defines important terms, variables, rules, and procedures required for solving a problem. Every step required to construct the problem solution can be defined in program commands that produce intermediate output. This paper advocates improved problem solving skills through using a programming tool. MatLab created by MathWorks, is an interactive numerical computing environment and programming language. It is a matrix-based system that easily lends itself to matrix manipulation, and plotting of functions and data. MatLab can be used as an interactive command line or a sequence of commands that can be saved in a file as a script or named functions. Prior programming experience is not required to use MatLab commands. The GNU Octave, part of the GNU project, a free computer program for performing numerical computations, is comparable to MatLab. MatLab visual and command programming are presented here.
Improve Problem Solving Skills through Adapting Programming Tools
NASA Technical Reports Server (NTRS)
Shaykhian, Linda H.; Shaykhian, Gholam Ali
2007-01-01
There are numerous ways for engineers and students to become better problem-solvers. The use of command line and visual programming tools can help to model a problem and formulate a solution through visualization. The analysis of problem attributes and constraints provide insight into the scope and complexity of the problem. The visualization aspect of the problem-solving approach tends to make students and engineers more systematic in their thought process and help them catch errors before proceeding too far in the wrong direction. The problem-solver identifies and defines important terms, variables, rules, and procedures required for solving a problem. Every step required to construct the problem solution can be defined in program commands that produce intermediate output. This paper advocates improved problem solving skills through using a programming tool. MatLab created by MathWorks, is an interactive numerical computing environment and programming language. It is a matrix-based system that easily lends itself to matrix manipulation, and plotting of functions and data. MatLab can be used as an interactive command line or a sequence of commands that can be saved in a file as a script or named functions. Prior programming experience is not required to use MatLab commands. The GNU Octave, part of the GNU project, a free computer program for performing numerical computations, is comparable to MatLab. MatLab visual and command programming are presented here.
The Tricomi problem of a quasi-linear Lavrentiev-Bitsadze mixed type equation
NASA Astrophysics Data System (ADS)
Shuxing, Chen; Zhenguo, Feng
2013-06-01
In this paper, we consider the Tricomi problem of a quasi-linear Lavrentiev-Bitsadze mixed type equation begin{array}{lll}(sgn u_y) {partial ^2 u/partial x^2} + {partial ^2 u/partial y^2}-1=0, whose coefficients depend on the first-order derivative of the unknown function. We prove the existence of solution to this problem by using the hodograph transformation. The method can be applied to study more difficult problems for nonlinear mixed type equations arising in gas dynamics.
A general algorithm for control problems with variable parameters and quasi-linear models
NASA Astrophysics Data System (ADS)
Bayón, L.; Grau, J. M.; Ruiz, M. M.; Suárez, P. M.
2015-12-01
This paper presents an algorithm that is able to solve optimal control problems in which the modelling of the system contains variable parameters, with the added complication that, in certain cases, these parameters can lead to control problems governed by quasi-linear equations. Combining the techniques of Pontryagin's Maximum Principle and the shooting method, an algorithm has been developed that is not affected by the values of the parameters, being able to solve conventional problems as well as cases in which the optimal solution is shown to be bang-bang with singular arcs.
Geometric tools for solving the FDI problem for linear periodic discrete-time systems
NASA Astrophysics Data System (ADS)
Longhi, Sauro; Monteriù, Andrea
2013-07-01
This paper studies the problem of detecting and isolating faults in linear periodic discrete-time systems. The aim is to design an observer-based residual generator where each residual is sensitive to one fault, whilst remaining insensitive to the other faults that can affect the system. Making use of the geometric tools, and in particular of the outer observable subspace notion, the Fault Detection and Isolation (FDI) problem is formulated and necessary and solvability conditions are given. An algorithmic procedure is described to determine the solution of the FDI problem.
DNA computation model to solve 0-1 programming problem.
Zhang, Fengyue; Yin, Zhixiang; Liu, Bo; Xu, Jin
2004-01-01
0-1 programming problem is an important problem in opsearch with very widespread applications. In this paper, a new DNA computation model utilizing solution-based and surface-based methods is presented to solve the 0-1 programming problem. This model contains the major benefits of both solution-based and surface-based methods; including vast parallelism, extraordinary information density and ease of operation. The result, verified by biological experimentation, revealed the potential of DNA computation in solving complex programming problem.
NASA Technical Reports Server (NTRS)
Kent, James; Holdaway, Daniel
2015-01-01
A number of geophysical applications require the use of the linearized version of the full model. One such example is in numerical weather prediction, where the tangent linear and adjoint versions of the atmospheric model are required for the 4DVAR inverse problem. The part of the model that represents the resolved scale processes of the atmosphere is known as the dynamical core. Advection, or transport, is performed by the dynamical core. It is a central process in many geophysical applications and is a process that often has a quasi-linear underlying behavior. However, over the decades since the advent of numerical modelling, significant effort has gone into developing many flavors of high-order, shape preserving, nonoscillatory, positive definite advection schemes. These schemes are excellent in terms of transporting the quantities of interest in the dynamical core, but they introduce nonlinearity through the use of nonlinear limiters. The linearity of the transport schemes used in Goddard Earth Observing System version 5 (GEOS-5), as well as a number of other schemes, is analyzed using a simple 1D setup. The linearized version of GEOS-5 is then tested using a linear third order scheme in the tangent linear version.
ERIC Educational Resources Information Center
Kim, SugHee; Chung, KwangSik; Yu, HeonChang
2013-01-01
The purpose of this paper is to propose a training program for creative problem solving based on computer programming. The proposed program will encourage students to solve real-life problems through a creative thinking spiral related to cognitive skills with computer programming. With the goal of enhancing digital fluency through this proposed…
ERIC Educational Resources Information Center
Kim, SugHee; Chung, KwangSik; Yu, HeonChang
2013-01-01
The purpose of this paper is to propose a training program for creative problem solving based on computer programming. The proposed program will encourage students to solve real-life problems through a creative thinking spiral related to cognitive skills with computer programming. With the goal of enhancing digital fluency through this proposed…
The linearized characteristics method and its application to practical nonlinear supersonic problems
NASA Technical Reports Server (NTRS)
Ferri, Antonio
1952-01-01
The methods of characteristics has been linearized by assuming that the flow field can be represented as a basic flow field determined by nonlinearized methods and a linearized superposed flow field that accounts for small changes of boundary conditions. The method has been applied to two-dimensional rotational flow where the basic flow is potential flow and to axially symmetric problems where conical flows have been used as the basic flows. In both cases the method allows the determination of the flow field to be simplified and the numerical work to be reduced to a few calculations. The calculations of axially symmetric flow can be simplified if tabulated values of some coefficients of the conical flow are obtained. The method has also been applied to slender bodies without symmetry and to some three-dimensional wing problems where two-dimensional flow can be used as the basic flow. Both problems were unsolved before in the approximation of nonlinear flow.
NASA Technical Reports Server (NTRS)
Arneson, Heather M.; Dousse, Nicholas; Langbort, Cedric
2014-01-01
We consider control design for positive compartmental systems in which each compartment's outflow rate is described by a concave function of the amount of material in the compartment.We address the problem of determining the routing of material between compartments to satisfy time-varying state constraints while ensuring that material reaches its intended destination over a finite time horizon. We give sufficient conditions for the existence of a time-varying state-dependent routing strategy which ensures that the closed-loop system satisfies basic network properties of positivity, conservation and interconnection while ensuring that capacity constraints are satisfied, when possible, or adjusted if a solution cannot be found. These conditions are formulated as a linear programming problem. Instances of this linear programming problem can be solved iteratively to generate a solution to the finite horizon routing problem. Results are given for the application of this control design method to an example problem. Key words: linear programming; control of networks; positive systems; controller constraints and structure.
Program Planning with Problem Mapping to Better Understand Need
ERIC Educational Resources Information Center
Forstadt, Leslie A.; Doore, Brian
2012-01-01
This article describes two methods for use in program development and refinement. Problem mapping and forcefield analysis are explained with a real-world example about parenting education. Both methods are visual and consider multiple causes and effects of a problem. The methods are effective for clearly thinking through a problem, identifying…
Program Planning with Problem Mapping to Better Understand Need
ERIC Educational Resources Information Center
Forstadt, Leslie A.; Doore, Brian
2012-01-01
This article describes two methods for use in program development and refinement. Problem mapping and forcefield analysis are explained with a real-world example about parenting education. Both methods are visual and consider multiple causes and effects of a problem. The methods are effective for clearly thinking through a problem, identifying…
Sun Wei; Huang, Guo H.; Lv Ying; Li Gongchen
2012-06-15
Highlights: Black-Right-Pointing-Pointer Inexact piecewise-linearization-based fuzzy flexible programming is proposed. Black-Right-Pointing-Pointer It's the first application to waste management under multiple complexities. Black-Right-Pointing-Pointer It tackles nonlinear economies-of-scale effects in interval-parameter constraints. Black-Right-Pointing-Pointer It estimates costs more accurately than the linear-regression-based model. Black-Right-Pointing-Pointer Uncertainties are decreased and more satisfactory interval solutions are obtained. - Abstract: To tackle nonlinear economies-of-scale (EOS) effects in interval-parameter constraints for a representative waste management problem, an inexact piecewise-linearization-based fuzzy flexible programming (IPFP) model is developed. In IPFP, interval parameters for waste amounts and transportation/operation costs can be quantified; aspiration levels for net system costs, as well as tolerance intervals for both capacities of waste treatment facilities and waste generation rates can be reflected; and the nonlinear EOS effects transformed from objective function to constraints can be approximated. An interactive algorithm is proposed for solving the IPFP model, which in nature is an interval-parameter mixed-integer quadratically constrained programming model. To demonstrate the IPFP's advantages, two alternative models are developed to compare their performances. One is a conventional linear-regression-based inexact fuzzy programming model (IPFP2) and the other is an IPFP model with all right-hand-sides of fussy constraints being the corresponding interval numbers (IPFP3). The comparison results between IPFP and IPFP2 indicate that the optimized waste amounts would have the similar patterns in both models. However, when dealing with EOS effects in constraints, the IPFP2 may underestimate the net system costs while the IPFP can estimate the costs more accurately. The comparison results between IPFP and IPFP3 indicate
Opportunities and Problems in Marketing Programs.
ERIC Educational Resources Information Center
Coe, Barbara J.; Welch, Joe
1988-01-01
A description and discussion of a university market penetration plan looks at problems and opportunities related to market selection, establishment of performance objectives, timing, use of human resources, developing a promotional plan and activities, doing a market survey, garnering alumni support, using the media, and using college-community…
Administrator Preparation Programs: Problems in Evaluating Competence.
ERIC Educational Resources Information Center
Kelley, Edgar A.
Judgments about competence are always relative, tentative, and situation-specific. An effective competency-based program for preparation of school administrators must base judgments about competency development on the same sources that will judge on-the-job administrative competency. The four most common instructional orientations to administrator…
Kim, D.; Ghanem, R.
1994-12-31
Multigrid solution technique to solve a material nonlinear problem in a visual programming environment using the finite element method is discussed. The nonlinear equation of equilibrium is linearized to incremental form using Newton-Rapson technique, then multigrid solution technique is used to solve linear equations at each Newton-Rapson step. In the process, adaptive mesh refinement, which is based on the bisection of a pair of triangles, is used to form grid hierarchy for multigrid iteration. The solution process is implemented in a visual programming environment with distributed computing capability, which enables more intuitive understanding of solution process, and more effective use of resources.
NASA Astrophysics Data System (ADS)
Veera Raghavan, Srikant
Semidefinite programming (SDP) is a relatively modern subfield of convex optimization which has been applied to many problems in the reduced density matrix (RDM) formulation of electronic structure. SDPs deal with minimization (or maximization) of linear objective functions of matrices, subject to linear equality and inequality constraints and positivity constraints on the eigenvalues of the matrices. Energies of chemical systems can be expressed as linear functions of RDMs, whose eigenvalues are electron occupation numbers or their products which are expected to be non-negative. Therefore, it is perhaps not surprising that SDPs fit rather naturally in the RDM framework in electronic structure. This dissertation presents SDP applications to two electronic structure theories. The first part of this dissertation (chaps. 1-3) reformulates Hartree-Fock theory in terms of SDPs in order to obtain upper and lower bounds to global Hartree-Fock energies. The upper and lower bounds on the energies are frequently equal thereby providing a first-ever certificate of global optimality for many Hartree-Fock solutions. The SDP approach provides an alternative to the conventional self-consistent field method of obtaining Hartree-Fock energies and densities with the added benefit of global optimality or a rigorous lower bound. Applications are made to the potential energy curves of (H 4)2, N2, C2, CN, Cr2 and NO2. Energies of the first-row transition elements are also calculated. In chapter 4, the effect of using the Hartree-Fock solutions that we calculate as references for coupled cluster singles doubles calculations is presented for some of the above molecules. The second part of this dissertation (chap. 5) presents a SDP approach to electronic structure methods which scale linearly with system size. Linear scaling electronic structure methods are essential in order to make calculations on large systems feasible. Among these methods the so-called density matrix based ones seek to
NASA Technical Reports Server (NTRS)
Wei, Peng; Sridhar, Banavar; Chen, Neil Yi-Nan; Sun, Dengfent
2012-01-01
A class of strategies has been proposed to reduce contrail formation in the United States airspace. A 3D grid based on weather data and the cruising altitude level of aircraft is adjusted to avoid the persistent contrail potential area with the consideration to fuel-efficiency. In this paper, the authors introduce a contrail avoidance strategy on 3D grid by considering additional operationally feasible constraints from an air traffic controller's aspect. First, shifting too many aircraft to the same cruising level will make the miles-in-trail at this level smaller than the safety separation threshold. Furthermore, the high density of aircraft at one cruising level may exceed the workload for the traffic controller. Therefore, in our new model we restrict the number of total aircraft at each level. Second, the aircraft count variation for successive intervals cannot be too drastic since the workload to manage climbing/descending aircraft is much larger than managing cruising aircraft. The contrail reduction is formulated as an integer-programming problem and the problem is shown to have the property of total unimodularity. Solving the corresponding relaxed linear programming with the simplex method provides an optimal and integral solution to the problem. Simulation results are provided to illustrate the methodology.
NASA Astrophysics Data System (ADS)
Qin, Chunbin; Zhang, Huaguang; Luo, Yanhong
2014-05-01
In this paper, a novel theoretic formulation based on adaptive dynamic programming (ADP) is developed to solve online the optimal tracking problem of the continuous-time linear system with unknown dynamics. First, the original system dynamics and the reference trajectory dynamics are transformed into an augmented system. Then, under the same performance index with the original system dynamics, an augmented algebraic Riccati equation is derived. Furthermore, the solutions for the optimal control problem of the augmented system are proven to be equal to the standard solutions for the optimal tracking problem of the original system dynamics. Moreover, a new online algorithm based on the ADP technique is presented to solve the optimal tracking problem of the linear system with unknown system dynamics. Finally, simulation results are given to verify the effectiveness of the theoretic results.
ERIC Educational Resources Information Center
Schmitt, M. A.; And Others
1994-01-01
Compares traditional manure application planning techniques calculated to meet agronomic nutrient needs on a field-by-field basis with plans developed using computer-assisted linear programming optimization methods. Linear programming provided the most economical and environmentally sound manure application strategy. (Contains 15 references.) (MDH)
ERIC Educational Resources Information Center
Schmitt, M. A.; And Others
1994-01-01
Compares traditional manure application planning techniques calculated to meet agronomic nutrient needs on a field-by-field basis with plans developed using computer-assisted linear programming optimization methods. Linear programming provided the most economical and environmentally sound manure application strategy. (Contains 15 references.) (MDH)
DRIESSEN,BRIAN; SADEGH,NADER
2000-04-25
This work presents a method of finding near global optima to minimum-time trajectory generation problem for systems that would be linear if it were not for the presence of Coloumb friction. The required final state of the system is assumed to be maintainable by the system, and the input bounds are assumed to be large enough so that they can overcome the maximum static Coloumb friction force. Other than the previous work for generating minimum-time trajectories for non redundant robotic manipulators for which the path in joint space is already specified, this work represents, to the best of the authors' knowledge, the first approach for generating near global optima for minimum-time problems involving a nonlinear class of dynamic systems. The reason the optima generated are near global optima instead of exactly global optima is due to a discrete-time approximation of the system (which is usually used anyway to simulate such a system numerically). The method closely resembles previous methods for generating minimum-time trajectories for linear systems, where the core operation is the solution of a Phase I linear programming problem. For the nonlinear systems considered herein, the core operation is instead the solution of a mixed integer linear programming problem.
Sun, Wei; Huang, Guo H; Lv, Ying; Li, Gongchen
2012-06-01
To tackle nonlinear economies-of-scale (EOS) effects in interval-parameter constraints for a representative waste management problem, an inexact piecewise-linearization-based fuzzy flexible programming (IPFP) model is developed. In IPFP, interval parameters for waste amounts and transportation/operation costs can be quantified; aspiration levels for net system costs, as well as tolerance intervals for both capacities of waste treatment facilities and waste generation rates can be reflected; and the nonlinear EOS effects transformed from objective function to constraints can be approximated. An interactive algorithm is proposed for solving the IPFP model, which in nature is an interval-parameter mixed-integer quadratically constrained programming model. To demonstrate the IPFP's advantages, two alternative models are developed to compare their performances. One is a conventional linear-regression-based inexact fuzzy programming model (IPFP2) and the other is an IPFP model with all right-hand-sides of fussy constraints being the corresponding interval numbers (IPFP3). The comparison results between IPFP and IPFP2 indicate that the optimized waste amounts would have the similar patterns in both models. However, when dealing with EOS effects in constraints, the IPFP2 may underestimate the net system costs while the IPFP can estimate the costs more accurately. The comparison results between IPFP and IPFP3 indicate that their solutions would be significantly different. The decreased system uncertainties in IPFP's solutions demonstrate its effectiveness for providing more satisfactory interval solutions than IPFP3. Following its first application to waste management, the IPFP can be potentially applied to other environmental problems under multiple complexities.
Solving Integer Programming Problems by Using Artificial Bee Colony Algorithm
NASA Astrophysics Data System (ADS)
Akay, Bahriye; Karaboga, Dervis
This paper presents a study that applies the Artificial Bee Colony algorithm to integer programming problems and compares its performance with those of Particle Swarm Optimization algorithm variants and Branch and Bound technique presented to the literature. In order to cope with integer programming problems, in neighbour solution production unit, solutions are truncated to the nearest integer values. The experimental results show that Artificial Bee Colony algorithm can handle integer programming problems efficiently and Artificial Bee Colony algorithm can be considered to be very robust by the statistics calculated such as mean, median, standard deviation.
A linear circuit analysis program with stiff systems capability
NASA Technical Reports Server (NTRS)
Cook, C. H.; Bavuso, S. J.
1973-01-01
Several existing network analysis programs have been modified and combined to employ a variable topological approach to circuit translation. Efficient numerical integration techniques are used for transient analysis.
An algorithm for the weighting matrices in the sampled-data optimal linear regulator problem
NASA Technical Reports Server (NTRS)
Armstrong, E. S.; Caglayan, A. K.
1976-01-01
The sampled-data optimal linear regulator problem provides a means whereby a control designer can use an understanding of continuous optimal regulator design to produce a digital state variable feedback control law which satisfies continuous system performance specifications. A basic difficulty in applying the sampled-data regulator theory is the requirement that certain digital performance index weighting matrices, expressed as complicated functions of system matrices, be computed. Infinite series representations are presented for the weighting matrices of the time-invariant version of the optimal linear sampled-data regulator problem. Error bounds are given for estimating the effect of truncating the series expressions after a finite number of terms, and a method is described for their computer implementation. A numerical example is given to illustrate the results.
Evaluation of boundary element methods for the EEG forward problem: Effect of linear interpolation
Schlitt, H.A.; Heller, L.; Best, E.; Ranken, D.M. ); Aaron, R. )
1995-01-01
We implement the approach for solving the boundary integral equation for the electroencephalography (EEG) forward problem proposed by de Munck, in which the electric potential varies linearly across each plane triangle of the mesh. Previous solutions have assumed the potential is constant across an element. We calculate the electric potential and systematically investigate the effect of different mesh choices and dipole locations by using a three concentric sphere head model for which there is an analytic solution. Implementing the linear interpolation approximation results in errors that are approximately half those of the same mesh when the potential is assumed to be constant, and provides a reliable method for solving the problem. 12 refs., 8 figs.
Well-posedness of the time-varying linear electromagnetic initial-boundary value problem
NASA Astrophysics Data System (ADS)
Xie, Li; Lei, Yin-Zhao
2007-09-01
The well-posedness of the initial-boundary value problem of the time-varying linear electromagnetic field in a multi-medium region is investigated. Function spaces are defined, with Faraday's law of electromagnetic induction and the initial-boundary conditions considered as constraints. Gauss's formula applied to a multi-medium region is used to derive the energy-estimating inequality. After converting the initial-boundary conditions into homogeneous ones and analysing the characteristics of an operator introduced according to the total current law, the existence, uniqueness and stability of the weak solution to the initial-boundary value problem of the time-varying linear electromagnetic field are proved.
NASA Astrophysics Data System (ADS)
Perrone, Antonio L.; Basti, Gianfranco
1995-04-01
With respect to Rosenblatt linear perceptron, two classical limitation theorems demonstrated by M. Minsky and S. Papert are discussed. These two theorems, `(Psi) One-in-a-box' and `(Psi) Parity,' ultimately concern the intrinsic limitations of parallel calculations in pattern recognition problems. We demonstrate a possible solution of these limitation problems by substituting the static definition of characteristic functions and of their domains in the `geometrical' perceptron, with their dynamic definition. This dynamic consists in the mutual redefinition of the characteristic function and of its domain depending on the matching with the input.
Solution of second order quasi-linear boundary value problems by a wavelet method
Zhang, Lei; Zhou, Youhe; Wang, Jizeng
2015-03-10
A wavelet Galerkin method based on expansions of Coiflet-like scaling function bases is applied to solve second order quasi-linear boundary value problems which represent a class of typical nonlinear differential equations. Two types of typical engineering problems are selected as test examples: one is about nonlinear heat conduction and the other is on bending of elastic beams. Numerical results are obtained by the proposed wavelet method. Through comparing to relevant analytical solutions as well as solutions obtained by other methods, we find that the method shows better efficiency and accuracy than several others, and the rate of convergence can even reach orders of 5.8.
NASA Technical Reports Server (NTRS)
Gibson, J. S.; Rosen, I. G.
1987-01-01
In the optimal linear quadratic regulator problem for finite dimensional systems, the method known as an alpha-shift can be used to produce a closed-loop system whose spectrum lies to the left of some specified vertical line; that is, a closed-loop system with a prescribed degree of stability. This paper treats the extension of the alpha-shift to hereditary systems. As infinite dimensions, the shift can be accomplished by adding alpha times the identity to the open-loop semigroup generator and then solving an optimal regulator problem. However, this approach does not work with a new approximation scheme for hereditary control problems recently developed by Kappel and Salamon. Since this scheme is among the best to date for the numerical solution of the linear regulator problem for hereditary systems, an alternative method for shifting the closed-loop spectrum is needed. An alpha-shift technique that can be used with the Kappel-Salamon approximation scheme is developed. Both the continuous-time and discrete-time problems are considered. A numerical example which demonstrates the feasibility of the method is included.
NASA Technical Reports Server (NTRS)
Gibson, J. S.; Rosen, I. G.
1985-01-01
In the optimal linear quadratic regulator problem for finite dimensional systems, the method known as an alpha-shift can be used to produce a closed-loop system whose spectrum lies to the left of some specified vertical line; that is, a closed-loop system with a prescribed degree of stability. This paper treats the extension of the alpha-shift to hereditary systems. As infinite dimensions, the shift can be accomplished by adding alpha times the identity to the open-loop semigroup generator and then solving an optimal regulator problem. However, this approach does not work with a new approximation scheme for hereditary control problems recently developed by Kappel and Salamon. Since this scheme is among the best to date for the numerical solution of the linear regulator problem for hereditary systems, an alternative method for shifting the closed-loop spectrum is needed. An alpha-shift technique that can be used with the Kappel-Salamon approximation scheme is developed. Both the continuous-time and discrete-time problems are considered. A numerical example which demonstrates the feasibility of the method is included.
NASA Technical Reports Server (NTRS)
Gibson, J. S.; Rosen, I. G.
1987-01-01
In the optimal linear quadratic regulator problem for finite dimensional systems, the method known as an alpha-shift can be used to produce a closed-loop system whose spectrum lies to the left of some specified vertical line; that is, a closed-loop system with a prescribed degree of stability. This paper treats the extension of the alpha-shift to hereditary systems. As infinite dimensions, the shift can be accomplished by adding alpha times the identity to the open-loop semigroup generator and then solving an optimal regulator problem. However, this approach does not work with a new approximation scheme for hereditary control problems recently developed by Kappel and Salamon. Since this scheme is among the best to date for the numerical solution of the linear regulator problem for hereditary systems, an alternative method for shifting the closed-loop spectrum is needed. An alpha-shift technique that can be used with the Kappel-Salamon approximation scheme is developed. Both the continuous-time and discrete-time problems are considered. A numerical example which demonstrates the feasibility of the method is included.
Promising Parenting Programs for Reducing Adolescent Problem Behaviors.
Haggerty, Kevin P; McGlynn-Wright, Anne; Klima, Tali
2013-01-01
Adolescent problem behaviors (substance use, delinquency, school dropout, pregnancy, and violence) are costly not only for individuals, but for entire communities. Policymakers and practitioners that are interested in preventing these problem behaviors are faced with many programming options. In this review, we discuss two criteria for selecting relevant parenting programs, and provide five examples of such programs. The first criterion for program selection is theory based. Well-supported theories, such as the social development model, have laid out key family-based risk and protective factors for problem behavior. Programs that target these risk and protective factors are more likely to be effective. Second, programs should have demonstrated efficacy; these interventions have been called "evidence-based programs" (EBP). This review highlights the importance of evidence from rigorous research designs, such as randomized clinical trials, in order to establish program efficacy. Nurse-Family Partnership, The Incredible Years, Positive Parenting Program, Strengthening Families 10-14, and Staying Connected with Your Teen are examined. The unique features of each program are briefly presented. Evidence showing impact on family risk and protective factors, as well as long-term problem behaviors, is reviewed. Finally, a measure of cost effectiveness of each program is provided. We propose that not all programs are of equal value, and suggest two simple criteria for selecting a parenting program with a high likelihood for positive outcomes. Furthermore, although this review is not exhaustive, the five examples of EBPs offer a good start for policymakers and practitioners seeking to implement effective programs in their communities. Thus, this paper offers practical suggestions for those grappling with investments in child and adolescent programs on the ground.
Lorber, A.A.; Carey, G.F.; Bova, S.W.; Harle, C.H.
1996-12-31
The connection between the solution of linear systems of equations by iterative methods and explicit time stepping techniques is used to accelerate to steady state the solution of ODE systems arising from discretized PDEs which may involve either physical or artificial transient terms. Specifically, a class of Runge-Kutta (RK) time integration schemes with extended stability domains has been used to develop recursion formulas which lead to accelerated iterative performance. The coefficients for the RK schemes are chosen based on the theory of Chebyshev iteration polynomials in conjunction with a local linear stability analysis. We refer to these schemes as Chebyshev Parameterized Runge Kutta (CPRK) methods. CPRK methods of one to four stages are derived as functions of the parameters which describe an ellipse {Epsilon} which the stability domain of the methods is known to contain. Of particular interest are two-stage, first-order CPRK and four-stage, first-order methods. It is found that the former method can be identified with any two-stage RK method through the correct choice of parameters. The latter method is found to have a wide range of stability domains, with a maximum extension of 32 along the real axis. Recursion performance results are presented below for a model linear convection-diffusion problem as well as non-linear fluid flow problems discretized by both finite-difference and finite-element methods.
A Conforming Multigrid Method for the Pure Traction Problem of Linear Elasticity: Mixed Formulation
NASA Technical Reports Server (NTRS)
Lee, Chang-Ock
1996-01-01
A multigrid method using conforming P-1 finite element is developed for the two-dimensional pure traction boundary value problem of linear elasticity. The convergence is uniform even as the material becomes nearly incompressible. A heuristic argument for acceleration of the multigrid method is discussed as well. Numerical results with and without this acceleration as well as performance estimates on a parallel computer are included.
NASA Technical Reports Server (NTRS)
Ito, Kazufumi; Teglas, Russell
1987-01-01
The numerical scheme based on the Legendre-tau approximation is proposed to approximate the feedback solution to the linear quadratic optimal control problem for hereditary differential systems. The convergence property is established using Trotter ideas. The method yields very good approximations at low orders and provides an approximation technique for computing closed-loop eigenvalues of the feedback system. A comparison with existing methods (based on averaging and spline approximations) is made.
NASA Technical Reports Server (NTRS)
Ito, K.; Teglas, R.
1984-01-01
The numerical scheme based on the Legendre-tau approximation is proposed to approximate the feedback solution to the linear quadratic optimal control problem for hereditary differential systems. The convergence property is established using Trotter ideas. The method yields very good approximations at low orders and provides an approximation technique for computing closed-loop eigenvalues of the feedback system. A comparison with existing methods (based on averaging and spline approximations) is made.
A Conforming Multigrid Method for the Pure Traction Problem of Linear Elasticity: Mixed Formulation
NASA Technical Reports Server (NTRS)
Lee, Chang-Ock
1996-01-01
A multigrid method using conforming P-1 finite element is developed for the two-dimensional pure traction boundary value problem of linear elasticity. The convergence is uniform even as the material becomes nearly incompressible. A heuristic argument for acceleration of the multigrid method is discussed as well. Numerical results with and without this acceleration as well as performance estimates on a parallel computer are included.
Robust parallel iterative solvers for linear and least-squares problems, Final Technical Report
Saad, Yousef
2014-01-16
The primary goal of this project is to study and develop robust iterative methods for solving linear systems of equations and least squares systems. The focus of the Minnesota team is on algorithms development, robustness issues, and on tests and validation of the methods on realistic problems. 1. The project begun with an investigation on how to practically update a preconditioner obtained from an ILU-type factorization, when the coefficient matrix changes. 2. We investigated strategies to improve robustness in parallel preconditioners in a specific case of a PDE with discontinuous coefficients. 3. We explored ways to adapt standard preconditioners for solving linear systems arising from the Helmholtz equation. These are often difficult linear systems to solve by iterative methods. 4. We have also worked on purely theoretical issues related to the analysis of Krylov subspace methods for linear systems. 5. We developed an effective strategy for performing ILU factorizations for the case when the matrix is highly indefinite. The strategy uses shifting in some optimal way. The method was extended to the solution of Helmholtz equations by using complex shifts, yielding very good results in many cases. 6. We addressed the difficult problem of preconditioning sparse systems of equations on GPUs. 7. A by-product of the above work is a software package consisting of an iterative solver library for GPUs based on CUDA. This was made publicly available. It was the first such library that offers complete iterative solvers for GPUs. 8. We considered another form of ILU which blends coarsening techniques from Multigrid with algebraic multilevel methods. 9. We have released a new version on our parallel solver - called pARMS [new version is version 3]. As part of this we have tested the code in complex settings - including the solution of Maxwell and Helmholtz equations and for a problem of crystal growth.10. As an application of polynomial preconditioning we considered the
Dyehouse, Melissa; Bennett, Deborah; Harbor, Jon; Childress, Amy; Dark, Melissa
2009-08-01
Logic models are based on linear relationships between program resources, activities, and outcomes, and have been used widely to support both program development and evaluation. While useful in describing some programs, the linear nature of the logic model makes it difficult to capture the complex relationships within larger, multifaceted programs. Causal loop diagrams based on a systems thinking approach can better capture a multidimensional, layered program model while providing a more complete understanding of the relationship between program elements, which enables evaluators to examine influences and dependencies between and within program components. Few studies describe how to conceptualize and apply systems models for educational program evaluation. The goal of this paper is to use our NSF-funded, Interdisciplinary GK-12 project: Bringing Authentic Problem Solving in STEM to Rural Middle Schools to illustrate a systems thinking approach to model a complex educational program to aid in evaluation. GK-12 pairs eight teachers with eight STEM doctoral fellows per program year to implement curricula in middle schools. We demonstrate how systems thinking provides added value by modeling the participant groups, instruments, outcomes, and other factors in ways that enhance the interpretation of quantitative and qualitative data. Limitations of the model include added complexity. Implications include better understanding of interactions and outcomes and analyses reflecting interacting or conflicting variables.
How Relevant Is Linear, Dichotomous Reasoning to Ongoing Program Evaluation?
ERIC Educational Resources Information Center
Nguyen, Tuan D.
1978-01-01
Criticizes Strasser and Deniston's post-planned evaluation (TM 504 253) because of their: (1) emphasis on evaluation research; (2) imposition of experimental rigor; (3) inapplicability to human service projects; (4) inattention to congruity between the program and its environment; (5) distinct characteristics of program evaluation; and (6)…
Effective radiological safety program for electron linear accelerators
Swanson, W.P.
1980-10-01
An outline is presented of some of the main elements of an electron accelerator radiological safety program. The discussion includes types of accelerator facilities, types of radiations to be anticipated, activity induced in components, air and water, and production of toxic gases. Concepts of radiation shielding design are briefly discussed and organizational aspects are considered as an integral part of the overall safety program.
Uncovering signal transduction networks from high-throughput data by integer linear programming.
Zhao, Xing-Ming; Wang, Rui-Sheng; Chen, Luonan; Aihara, Kazuyuki
2008-05-01
Signal transduction is an important process that transmits signals from the outside of a cell to the inside to mediate sophisticated biological responses. Effective computational models to unravel such a process by taking advantage of high-throughput genomic and proteomic data are needed to understand the essential mechanisms underlying the signaling pathways. In this article, we propose a novel method for uncovering signal transduction networks (STNs) by integrating protein interaction with gene expression data. Specifically, we formulate STN identification problem as an integer linear programming (ILP) model, which can be actually solved by a relaxed linear programming algorithm and is flexible for handling various prior information without any restriction on the network structures. The numerical results on yeast MAPK signaling pathways demonstrate that the proposed ILP model is able to uncover STNs or pathways in an efficient and accurate manner. In particular, the prediction results are found to be in high agreement with current biological knowledge and available information in literature. In addition, the proposed model is simple to be interpreted and easy to be implemented even for a large-scale system.
Radial-interval linear programming for environmental management under varied protection levels.
Tan, Qian; Huang, Guo H; Cai, Yanpeng
2010-09-01
In this study, a radial-interval linear programming (RILP) approach was developed for supporting waste management under uncertainty. RILP improved interval-parameter linear programming and its extensions in terms of input reasonableness and output robustness. From the perspective of modeling inputs, RILP could tackle highly uncertain information at the bounds of interval parameters through introducing the concept of fluctuation radius. Regarding modeling outputs, RILP allows controlling the degree of conservatism associated with interval solutions and is capable of quantifying corresponding system risks and benefits. This could facilitate the reflection of interactive relationship between the feasibility of system and the uncertainty of parameters. A computationally tractable algorithm was provided to solve RILP. Then, a long-term waste management case was studied to demonstrate the applicability of the developed methodology. A series of interval solutions obtained under varied protection levels were compared, helping gain insights into the interactions among protection level, violation risk, and system cost. Potential waste allocation alternatives could be generated from these interval solutions, which would be screened in real-world practices according to various projected system conditions as well as decision-makers' willingness to pay and risk tolerance levels. Sensitivity analysis further revealed the significant impact of fluctuation radii of interval parameters on the system. The results indicated that RILP is applicable to a wide spectrum of environmental management problems that are subject to compound uncertainties.
Dual mean field search for large scale linear and quadratic knapsack problems
NASA Astrophysics Data System (ADS)
Banda, Juan; Velasco, Jonás; Berrones, Arturo
2017-07-01
An implementation of mean field annealing to deal with large scale linear and non linear binary optimization problems is given. Mean field annealing is based on the analogy between combinatorial optimization and interacting physical systems at thermal equilibrium. Specifically, a mean field approximation of the Boltzmann distribution given by a Lagrangian that encompass the objective function and the constraints is calculated. The original discrete task is in this way transformed into a continuous variational problem. In our version of mean field annealing, no temperature parameter is used, but a good starting point in the dual space is given by a ;thermodynamic limit; argument. The method is tested in linear and quadratic knapsack problems with sizes that are considerably larger than those used in previous studies of mean field annealing. Dual mean field annealing is capable to find high quality solutions in running times that are orders of magnitude shorter than state of the art algorithms. Moreover, as may be expected for a mean field theory, the solutions tend to be more accurate as the number of variables grow.
NASA Technical Reports Server (NTRS)
Fleming, P.
1985-01-01
A design technique is proposed for linear regulators in which a feedback controller of fixed structure is chosen to minimize an integral quadratic objective function subject to the satisfaction of integral quadratic constraint functions. Application of a non-linear programming algorithm to this mathematically tractable formulation results in an efficient and useful computer-aided design tool. Particular attention is paid to computational efficiency and various recommendations are made. Two design examples illustrate the flexibility of the approach and highlight the special insight afforded to the designer.
NASA Technical Reports Server (NTRS)
Fleming, P.
1985-01-01
A design technique is proposed for linear regulators in which a feedback controller of fixed structure is chosen to minimize an integral quadratic objective function subject to the satisfaction of integral quadratic constraint functions. Application of a non-linear programming algorithm to this mathematically tractable formulation results in an efficient and useful computer-aided design tool. Particular attention is paid to computational efficiency and various recommendations are made. Two design examples illustrate the flexibility of the approach and highlight the special insight afforded to the designer.
Symbolic programming language in molecular multicenter integral problem
NASA Astrophysics Data System (ADS)
Safouhi, Hassan; Bouferguene, Ahmed
It is well known that in any ab initio molecular orbital (MO) calculation, the major task involves the computation of molecular integrals, among which the computation of three-center nuclear attraction and Coulomb integrals is the most frequently encountered. As the molecular system becomes larger, computation of these integrals becomes one of the most laborious and time-consuming steps in molecular systems calculation. Improvement of the computational methods of molecular integrals would be indispensable to further development in computational studies of large molecular systems. To develop fast and accurate algorithms for the numerical evaluation of these integrals over B functions, we used nonlinear transformations for improving convergence of highly oscillatory integrals. These methods form the basis of new methods for solving various problems that were unsolvable otherwise and have many applications as well. To apply these nonlinear transformations, the integrands should satisfy linear differential equations with coefficients having asymptotic power series in the sense of Poincaré, which in their turn should satisfy some limit conditions. These differential equations are very difficult to obtain explicitly. In the case of molecular integrals, we used a symbolic programming language (MAPLE) to demonstrate that all the conditions required to apply these nonlinear transformation methods are satisfied. Differential equations are obtained explicitly, allowing us to demonstrate that the limit conditions are also satisfied.
Measurement problem in Program Universe. Revision
Noyes, H.P.; Gefwert, C.; Manthey, M.J.
1985-07-01
The ''measurement problem'' of contemporary physics is in our view an artifact of its philosophical and mathematical underpinnings. We describe a new philosophical view of theory formation, rooted in Wittgenstein, and Bishop's and Martin-Loef's constructivity, which obviates such discussions. We present an unfinished, but very encouraging, theory which is compatible with this philosophical framework. The theory is based on the concepts of counting and combinatorics in the framework provided by the combinatorial hierarchy, a unique hierarchy of bit strings which interact by an operation called discrimination. Measurement criteria incorporate c, h-bar and m/sub p/ or (not ''and'') G. The resulting theory is discrete throughout, contains no infinities, and, as far as we have developed it, is in agreement with quantum mechanical and cosmological fact. 15 refs.
Measurement problem in Program Universe. Revision
NASA Astrophysics Data System (ADS)
Noyes, H. P.; Gefwert, C.; Manthey, M. J.
1985-07-01
The measurement problem of contemporary physics is in our view an artifact of its philosophical and mathematical underpinnings. We describe a new philosophical view of theory formation, rooted in Wittgenstein, and Bishop's and Martin-Loef's constructivity, which obviates such discussions. We present an unfinished, but very encouraging, theory which is compatible with this philosophical framework. The theory is based on the concepts of counting and combinatorics in the framework provided by the combinatorial hierarchy, a unique hierarchy of bit strings which interact by an operation called discrimination. Measurement criteria incorporate c, h-bar and m/sub p/ or (not and) G. The resulting theory is discrete throughout, contains no infinities, and, as far as we have developed it, is in agreement with quantum mechanical and cosmological fact.
Promising Parenting Programs for Reducing Adolescent Problem Behaviors
Haggerty, Kevin P.; McGlynn-Wright, Anne; Klima, Tali
2013-01-01
Purpose Adolescent problem behaviors (substance use, delinquency, school dropout, pregnancy, and violence) are costly not only for individuals, but for entire communities. Policymakers and practitioners that are interested in preventing these problem behaviors are faced with many programming options. In this review, we discuss two criteria for selecting relevant parenting programs, and provide five examples of such programs. Design/methodology/approach The first criterion for program selection is theory based. Well-supported theories, such as the social development model, have laid out key family-based risk and protective factors for problem behavior. Programs that target these risk and protective factors are more likely to be effective. Second, programs should have demonstrated efficacy; these interventions have been called “evidence-based programs” (EBP). This review highlights the importance of evidence from rigorous research designs, such as randomized clinical trials, in order to establish program efficacy. Findings Nurse-Family Partnership, The Incredible Years, Positive Parenting Program, Strengthening Families 10–14, and Staying Connected with Your Teen are examined. The unique features of each program are briefly presented. Evidence showing impact on family risk and protective factors, as well as long-term problem behaviors, is reviewed. Finally, a measure of cost effectiveness of each program is provided. Originality/value We propose that not all programs are of equal value, and suggest two simple criteria for selecting a parenting program with a high likelihood for positive outcomes. Furthermore, although this review is not exhaustive, the five examples of EBPs offer a good start for policymakers and practitioners seeking to implement effective programs in their communities. Thus, this paper offers practical suggestions for those grappling with investments in child and adolescent programs on the ground. PMID:24416068
The Environmental Justice Collaborative Problem-Solving Cooperative Agreement Program
The Environmental Justice Collaborative Problem-Solving (CPS) Cooperative Agreement Program provides financial assistance to eligible organizations working on or planning to work on projects to address local environmental and/or public health issues
Serang, Oliver
2012-01-01
Linear programming (LP) problems are commonly used in analysis and resource allocation, frequently surfacing as approximations to more difficult problems. Existing approaches to LP have been dominated by a small group of methods, and randomized algorithms have not enjoyed popularity in practice. This paper introduces a novel randomized method of solving LP problems by moving along the facets and within the interior of the polytope along rays randomly sampled from the polyhedral cones defined by the bounding constraints. This conic sampling method is then applied to randomly sampled LPs, and its runtime performance is shown to compare favorably to the simplex and primal affine-scaling algorithms, especially on polytopes with certain characteristics. The conic sampling method is then adapted and applied to solve a certain quadratic program, which compute a projection onto a polytope; the proposed method is shown to outperform the proprietary software Mathematica on large, sparse QP problems constructed from mass spectometry-based proteomics. PMID:22952741
Serang, Oliver
2012-01-01
Linear programming (LP) problems are commonly used in analysis and resource allocation, frequently surfacing as approximations to more difficult problems. Existing approaches to LP have been dominated by a small group of methods, and randomized algorithms have not enjoyed popularity in practice. This paper introduces a novel randomized method of solving LP problems by moving along the facets and within the interior of the polytope along rays randomly sampled from the polyhedral cones defined by the bounding constraints. This conic sampling method is then applied to randomly sampled LPs, and its runtime performance is shown to compare favorably to the simplex and primal affine-scaling algorithms, especially on polytopes with certain characteristics. The conic sampling method is then adapted and applied to solve a certain quadratic program, which compute a projection onto a polytope; the proposed method is shown to outperform the proprietary software Mathematica on large, sparse QP problems constructed from mass spectometry-based proteomics.
Programmable calculator program for linear somatic cell scores to estimate mastitis yield losses.
Kirk, J H
1984-02-01
A programmable calculator program calculates loss of milk yield in dairy cows based on linear somatic cell count scores. The program displays the distribution of the herd by lactation number and linear score for present and optimal goal situations. Loss of yield is in pounds and dollars by cow and herd. The program estimates optimal milk production and numbers of fewer cows at the goal for mastitis infection.
Dang, Chuangyin; Liang, Jianqing; Yang, Yang
2013-03-01
A deterministic annealing algorithm is proposed for approximating a solution of the linearly constrained nonconvex quadratic minimization problem. The algorithm is derived from applications of a Hopfield-type barrier function in dealing with box constraints and Lagrange multipliers in handling linear equality constraints, and attempts to obtain a solution of good quality by generating a minimum point of a barrier problem for a sequence of descending values of the barrier parameter. For any given value of the barrier parameter, the algorithm searches for a minimum point of the barrier problem in a feasible descent direction, which has a desired property that the box constraints are always satisfied automatically if the step length is a number between zero and one. At each iteration, the feasible descent direction is found by updating Lagrange multipliers with a globally convergent iterative procedure. For any given value of the barrier parameter, the algorithm converges to a stationary point of the barrier problem. Preliminary numerical results show that the algorithm seems effective and efficient. Copyright © 2012 Elsevier Ltd. All rights reserved.
Determination of Interspin Distance Distributions by cw-ESR Is a Single Linear Inverse Problem
Chiang, Yun-Wei; Zheng, Tong-Yuan; Kao, Chiao-Jung; Horng, Jia-Cherng
2009-01-01
Abstract Cw-ESR distance measurement method is extremely valuable for studying the dynamics-function relationship of biomolecules. However, extracting distance distributions from experiments has been a highly technique-demanding procedure. It has never been conclusively identified, to our knowledge, that the problems involved in the analysis are ill posed and are best solved using Tikhonov regularization. We treat the problems from a novel point of view. First of all, we identify the equations involved and uncover that they are actually two linear first-kind Fredholm integral equations. They can be combined into one single linear inverse problem and solved in a Tikhonov regularization procedure. The improvement with our new treatment is significant. Our approach is a direct and reliable mathematical method capable of providing an unambiguous solution to the ill-posed problem. It need not perform nonlinear least-squares fitting to infer a solution from noise-contaminated data and, accordingly, substantially reduces the computation time and the difficulty of analysis. Numerical tests and experimental data of polyproline II peptides with variant spin-labeled sites are provided to demonstrate our approach. The high resolution of the distance distributions obtainable with our new approach enables a detailed insight into the flexibility of dynamic structure and the identification of conformational species in solution state. PMID:19651052
Arbitrary Lagrangian-Eulerian method for non-linear problems of geomechanics
NASA Astrophysics Data System (ADS)
Nazem, M.; Carter, J. P.; Airey, D. W.
2010-06-01
In many geotechnical problems it is vital to consider the geometrical non-linearity caused by large deformation in order to capture a more realistic model of the true behaviour. The solutions so obtained should then be more accurate and reliable, which should ultimately lead to cheaper and safer design. The Arbitrary Lagrangian-Eulerian (ALE) method originated from fluid mechanics, but has now been well established for solving large deformation problems in geomechanics. This paper provides an overview of the ALE method and its challenges in tackling problems involving non-linearities due to material behaviour, large deformation, changing boundary conditions and time-dependency, including material rate effects and inertia effects in dynamic loading applications. Important aspects of ALE implementation into a finite element framework will also be discussed. This method is then employed to solve some interesting and challenging geotechnical problems such as the dynamic bearing capacity of footings on soft soils, consolidation of a soil layer under a footing, and the modelling of dynamic penetration of objects into soil layers.
A primary shift rotation nurse scheduling using zero-one linear goal programming.
Huarng, F
1999-01-01
In this study, the author discusses the effect of nurse shift schedules on circadian rhythm and some important ergonomics criteria. The author also reviews and compares different nurse shift scheduling methods via the criteria of flexibility, fairness, continuity in shift assignments, nurses' preferences, and ergonomics principles. In this article, a primary shift rotation system is proposed to provide better continuity in shift assignments to satisfy nurses' preferences. The primary shift rotation system is modeled as a zero-one linear goal programming (LGP) problem. To generate the shift assignment for a unit with 13 nurses, the zero-one LGP model takes less than 3 minutes on average, whereas the head nurses spend approximately 2 to 3 hours on shift scheduling. This study reports the process of implementing the primary shift rotation system.
Continuous-time Q-learning for infinite-horizon discounted cost linear quadratic regulator problems.
Palanisamy, Muthukumar; Modares, Hamidreza; Lewis, Frank L; Aurangzeb, Muhammad
2015-02-01
This paper presents a method of Q-learning to solve the discounted linear quadratic regulator (LQR) problem for continuous-time (CT) continuous-state systems. Most available methods in the existing literature for CT systems to solve the LQR problem generally need partial or complete knowledge of the system dynamics. Q-learning is effective for unknown dynamical systems, but has generally been well understood only for discrete-time systems. The contribution of this paper is to present a Q-learning methodology for CT systems which solves the LQR problem without having any knowledge of the system dynamics. A natural and rigorous justified parameterization of the Q-function is given in terms of the state, the control input, and its derivatives. This parameterization allows the implementation of an online Q-learning algorithm for CT systems. The simulation results supporting the theoretical development are also presented.
A Linear Time Algorithm for the Minimum Spanning Caterpillar Problem for Bounded Treewidth Graphs
NASA Astrophysics Data System (ADS)
Dinneen, Michael J.; Khosravani, Masoud
We consider the Minimum Spanning Caterpillar Problem (MSCP) in a graph where each edge has two costs, spine (path) cost and leaf cost, depending on whether it is used as a spine or a leaf edge. The goal is to find a spanning caterpillar in which the sum of its edge costs is the minimum. We show that the problem has a linear time algorithm when a tree decomposition of the graph is given as part of the input. Despite the fast growing constant factor of the time complexity of our algorithm, it is still practical and efficient for some classes of graphs, such as outerplanar, series-parallel (K 4 minor-free), and Halin graphs. We also briefly explain how one can modify our algorithm to solve the Minimum Spanning Ring Star and the Dual Cost Minimum Spanning Tree Problems.
Projection-free parallel quadratic programming for linear model predictive control
NASA Astrophysics Data System (ADS)
Di Cairano, S.; Brand, M.; Bortoff, S. A.
2013-08-01
A key component in enabling the application of model predictive control (MPC) in fields such as automotive, aerospace, and factory automation is the availability of low-complexity fast optimisation algorithms to solve the MPC finite horizon optimal control problem in architectures with reduced computational capabilities. In this paper, we introduce a projection-free iterative optimisation algorithm and discuss its application to linear MPC. The algorithm, originally developed by Brand for non-negative quadratic programs, is based on a multiplicative update rule and it is shown to converge to a fixed point which is the optimum. An acceleration technique based on a projection-free line search is also introduced, to speed-up the convergence to the optimum. The algorithm is applied to MPC through the dual of the quadratic program (QP) formulated from the MPC finite time optimal control problem. We discuss how termination conditions with guaranteed degree of suboptimality can be enforced, and how the algorithm performance can be optimised by pre-computing the matrices in a parametric form. We show computational results of the algorithm in three common case studies and we compare such results with the results obtained by other available free and commercial QP solvers.
Problem Solving Variations in an Online Programming Course
ERIC Educational Resources Information Center
Ebrahimi, Alireza
2007-01-01
An observation on teaching introductory programming courses on SLN for a period of two terms led me to believe that online students try various ways to solve a problem. In the beginning, I got the impression that some of their approaches for a solution were wrong; but after a little investigation, I found that some of the problem-solving…
Solving quadratic programming problems by delayed projection neural network.
Yang, Yongqing; Cao, Jinde
2006-11-01
In this letter, the delayed projection neural network for solving convex quadratic programming problems is proposed. The neural network is proved to be globally exponentially stable and can converge to an optimal solution of the optimization problem. Three examples show the effectiveness of the proposed network.
Experiences in Rural Mental Health. VIII: Programming and Administrative Problems.
ERIC Educational Resources Information Center
Hollister, William G.; And Others
Based on a North Carolina Feasibility study (1967-73) which focused on development of a pattern for providing comprehensive mental health services to rural people, this guide deals with programming and administrative problems in Vance and Franklin counties. Describing those problems believed to be most likely to occur in rural areas, this booklet…
Changing the Composition Program: A Problem-Solving Approach.
ERIC Educational Resources Information Center
Soven, Margot
Little attention has been paid in composition journals and professional conferences to the practical problems associated with a writing program director's efforts to introduce an innovative composition curriculum within a traditional English department. A collaborative, problem solving approach to curriculum change is a practical way to proceed…
Problems in Choosing Tools and Methods for Teaching Programming
ERIC Educational Resources Information Center
Vitkute-Adžgauskiene, Davia; Vidžiunas, Antanas
2012-01-01
The paper analyses the problems in selecting and integrating tools for delivering basic programming knowledge at the university level. Discussion and analysis of teaching the programming disciplines, the main principles of study programme design, requirements for teaching tools, methods and corresponding languages is presented, based on literature…
An Interdisciplinary Program in Technical Communications: Problems Encountered.
ERIC Educational Resources Information Center
Eckman, Martha
1979-01-01
Notes three major types of problems encountered by colleges and universities attempting to establish a program in technical communications: society's increasing need for better communications; industry's reluctance to fund cooperative programs; and difficulties within the academic community involving course selection, intercollegial competition…
Using Problem Solving to Teach a Programming Language.
ERIC Educational Resources Information Center
Milbrandt, George
1995-01-01
Computer studies courses should incorporate as many computer concepts and programming language experiences as possible. A gradual increase in problem difficulty will help the student to understand various computer concepts, and the programming language's syntax and structure. A sidebar provides two examples of how to establish a learning…
Pupil Personnel Services: A Model. Programs, Trends, Problems.
ERIC Educational Resources Information Center
Shumake, Franklin
As an attempt is made to develop pupil personnel programs throughout the United States, one faces many diverse problems: (1) diversity of background for pupil personnel specialists, (2) professional acceptance of other educators, (3) crystallization of purposes, and (4) need for a model program. The Rockdale County model is discussed in terms of…
Zhidkov, P E
2000-04-30
For a non-linear eigenvalue problem similar to a linear Sturm-Liouville problem the properties of the spectrum and the eigenfunctions are analysed. The system of eigenfunctions is shown to be a Riesz basis in L{sub 2}.
Boundary parametric approximation to the linearized scalar potential magnetostatic field problem
Bramble, J.H.; Pasciak, J.E.
1984-01-01
We consider the linearized scalar potential formulation of the magnetostatic field problem in this paper. Our approach involves a reformulation of the continuous problem as a parametric boundary problem. By the introduction of a spherical interface and the use of spherical harmonics, the infinite boundary conditions can also be satisfied in the parametric framework. That is, the field in the exterior of a sphere is expanded in a harmonic series of eigenfunctions for the exterior harmonic problem. The approach is essentially a finite element method coupled with a spectral method via a boundary parametric procedure. The reformulated problem is discretized by finite element techniques which lead to a discrete parametric problem which can be solved by well conditioned iteration involving only the solution of decoupled Neumann type elliptic finite element systems and L/sup 2/ projection onto subspaces of spherical harmonics. Error and stability estimates given show exponential convergence in the degree of the spherical harmonics and optimal order convergence with respect to the finite element approximation for the resulting fields in L/sup 2/. 24 references.
A linear programming approach for placement of applicants to academic programs.
Kassa, Biniyam Asmare
2013-01-01
This paper reports a linear programming approach for placement of applicants to study programs developed and implemented at the college of Business & Economics, Bahir Dar University, Bahir Dar, Ethiopia. The approach is estimated to significantly streamline the placement decision process at the college by reducing required man hour as well as the time it takes to announce placement decisions. Compared to the previous manual system where only one or two placement criteria were considered, the new approach allows the college's management to easily incorporate additional placement criteria, if needed. Comparison of our approach against manually constructed placement decisions based on actual data for the 2012/13 academic year suggested that about 93 percent of the placements from our model concur with the actual placement decisions. For the remaining 7 percent of placements, however, the actual placements made by the manual system display inconsistencies of decisions judged against the very criteria intended to guide placement decisions by the college's program management office. Overall, the new approach proves to be a significant improvement over the manual system in terms of efficiency of the placement process and the quality of placement decisions.
Kew, William; Mitchell, John B O
2015-09-01
The application of Machine Learning to cheminformatics is a large and active field of research, but there exist few papers which discuss whether ensembles of different Machine Learning methods can improve upon the performance of their component methodologies. Here we investigated a variety of methods, including kernel-based, tree, linear, neural networks, and both greedy and linear ensemble methods. These were all tested against a standardised methodology for regression with data relevant to the pharmaceutical development process. This investigation focused on QSPR problems within drug-like chemical space. We aimed to investigate which methods perform best, and how the 'wisdom of crowds' principle can be applied to ensemble predictors. It was found that no single method performs best for all problems, but that a dynamic, well-structured ensemble predictor would perform very well across the board, usually providing an improvement in performance over the best single method. Its use of weighting factors allows the greedy ensemble to acquire a bigger contribution from the better performing models, and this helps the greedy ensemble generally to outperform the simpler linear ensemble. Choice of data preprocessing methodology was found to be crucial to performance of each method too. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
The Use of Linear (Goal) Programming in the Construction of a Test Blueprint.
ERIC Educational Resources Information Center
Busch, John Christian; Taylor, Raymond G.
The use of a variation of linear programing (goal programing) to develop a test blueprint with multiple specification requirements, is the topic of this paper. The computer program STORM was used to develop a table of test specifications for a test that would measure achievement in introductory statistics in the subdomains of frequency…
Optimization of HDR brachytherapy dose distributions using linear programming with penalty costs
Alterovitz, Ron; Lessard, Etienne; Pouliot, Jean; Hsu, I-Chow Joe; O'Brien, James F.; Goldberg, Ken
2006-11-15
Prostate cancer is increasingly treated with high-dose-rate (HDR) brachytherapy, a type of radiotherapy in which a radioactive source is guided through catheters temporarily implanted in the prostate. Clinicians must set dwell times for the source inside the catheters so the resulting dose distribution minimizes deviation from dose prescriptions that conform to patient-specific anatomy. The primary contribution of this paper is to take the well-established dwell times optimization problem defined by Inverse Planning by Simulated Annealing (IPSA) developed at UCSF and exactly formulate it as a linear programming (LP) problem. Because LP problems can be solved exactly and deterministically, this formulation provides strong performance guarantees: one can rapidly find the dwell times solution that globally minimizes IPSA's objective function for any patient case and clinical criteria parameters. For a sample of 20 prostates with volume ranging from 23 to 103 cc, the new LP method optimized dwell times in less than 15 s per case on a standard PC. The dwell times solutions currently being obtained clinically using simulated annealing (SA), a probabilistic method, were quantitatively compared to the mathematically optimal solutions obtained using the LP method. The LP method resulted in significantly improved objective function values compared to SA (P=1.54x10{sup -7}), but none of the dosimetric indices indicated a statistically significant difference (P<0.01). The results indicate that solutions generated by the current version of IPSA are clinically equivalent to the mathematically optimal solutions.
Integer Linear Programming for Constrained Multi-Aspect Committee Review Assignment.
Karimzadehgan, Maryam; Zhai, Chengxiang
2012-07-01
Automatic review assignment can significantly improve the productivity of many people such as conference organizers, journal editors and grant administrators. A general setup of the review assignment problem involves assigning a set of reviewers on a committee to a set of documents to be reviewed under the constraint of review quota so that the reviewers assigned to a document can collectively cover multiple topic aspects of the document. No previous work has addressed such a setup of committee review assignments while also considering matching multiple aspects of topics and expertise. In this paper, we tackle the problem of committee review assignment with multi-aspect expertise matching by casting it as an integer linear programming problem. The proposed algorithm can naturally accommodate any probabilistic or deterministic method for modeling multiple aspects to automate committee review assignments. Evaluation using a multi-aspect review assignment test set constructed using ACM SIGIR publications shows that the proposed algorithm is effective and efficient for committee review assignments based on multi-aspect expertise matching.
Efficient linear programming algorithm to generate the densest lattice sphere packings.
Marcotte, Étienne; Torquato, Salvatore
2013-06-01
Finding the densest sphere packing in d-dimensional Euclidean space R(d) is an outstanding fundamental problem with relevance in many fields, including the ground states of molecular systems, colloidal crystal structures, coding theory, discrete geometry, number theory, and biological systems. Numerically generating the densest sphere packings becomes very challenging in high dimensions due to an exponentially increasing number of possible sphere contacts and sphere configurations, even for the restricted problem of finding the densest lattice sphere packings. In this paper we apply the Torquato-Jiao packing algorithm, which is a method based on solving a sequence of linear programs, to robustly reproduce the densest known lattice sphere packings for dimensions 2 through 19. We show that the TJ algorithm is appreciably more efficient at solving these problems than previously published methods. Indeed, in some dimensions, the former procedure can be as much as three orders of magnitude faster at finding the optimal solutions than earlier ones. We also study the suboptimal local density-maxima solutions (inherent structures or "extreme" lattices) to gain insight about the nature of the topography of the "density" landscape.
Integer Linear Programming for Constrained Multi-Aspect Committee Review Assignment
Karimzadehgan, Maryam; Zhai, ChengXiang
2011-01-01
Automatic review assignment can significantly improve the productivity of many people such as conference organizers, journal editors and grant administrators. A general setup of the review assignment problem involves assigning a set of reviewers on a committee to a set of documents to be reviewed under the constraint of review quota so that the reviewers assigned to a document can collectively cover multiple topic aspects of the document. No previous work has addressed such a setup of committee review assignments while also considering matching multiple aspects of topics and expertise. In this paper, we tackle the problem of committee review assignment with multi-aspect expertise matching by casting it as an integer linear programming problem. The proposed algorithm can naturally accommodate any probabilistic or deterministic method for modeling multiple aspects to automate committee review assignments. Evaluation using a multi-aspect review assignment test set constructed using ACM SIGIR publications shows that the proposed algorithm is effective and efficient for committee review assignments based on multi-aspect expertise matching. PMID:22711970
Acceleration of multiple solution of a boundary value problem involving a linear algebraic system
NASA Astrophysics Data System (ADS)
Gazizov, Talgat R.; Kuksenko, Sergey P.; Surovtsev, Roman S.
2016-06-01
Multiple solution of a boundary value problem that involves a linear algebraic system is considered. New approach to acceleration of the solution is proposed. The approach uses the structure of the linear system matrix. Particularly, location of entries in the right columns and low rows of the matrix, which undergo variation due to the computing in the range of parameters, is used to apply block LU decomposition. Application of the approach is considered on the example of multiple computing of the capacitance matrix by method of moments used in numerical electromagnetics. Expressions for analytic estimation of the acceleration are presented. Results of the numerical experiments for solution of 100 linear systems with matrix orders of 1000, 2000, 3000 and different relations of variated and constant entries of the matrix show that block LU decomposition can be effective for multiple solution of linear systems. The speed up compared to pointwise LU factorization increases (up to 15) for larger number and order of considered systems with lower number of variated entries.
NASA Astrophysics Data System (ADS)
Auger-Méthé, Marie; Field, Chris; Albertsen, Christoffer M.; Derocher, Andrew E.; Lewis, Mark A.; Jonsen, Ian D.; Mills Flemming, Joanna
2016-05-01
State-space models (SSMs) are increasingly used in ecology to model time-series such as animal movement paths and population dynamics. This type of hierarchical model is often structured to account for two levels of variability: biological stochasticity and measurement error. SSMs are flexible. They can model linear and nonlinear processes using a variety of statistical distributions. Recent ecological SSMs are often complex, with a large number of parameters to estimate. Through a simulation study, we show that even simple linear Gaussian SSMs can suffer from parameter- and state-estimation problems. We demonstrate that these problems occur primarily when measurement error is larger than biological stochasticity, the condition that often drives ecologists to use SSMs. Using an animal movement example, we show how these estimation problems can affect ecological inference. Biased parameter estimates of a SSM describing the movement of polar bears (Ursus maritimus) result in overestimating their energy expenditure. We suggest potential solutions, but show that it often remains difficult to estimate parameters. While SSMs are powerful tools, they can give misleading results and we urge ecologists to assess whether the parameters can be estimated accurately before drawing ecological conclusions from their results.
Auger-Méthé, Marie; Field, Chris; Albertsen, Christoffer M; Derocher, Andrew E; Lewis, Mark A; Jonsen, Ian D; Mills Flemming, Joanna
2016-05-25
State-space models (SSMs) are increasingly used in ecology to model time-series such as animal movement paths and population dynamics. This type of hierarchical model is often structured to account for two levels of variability: biological stochasticity and measurement error. SSMs are flexible. They can model linear and nonlinear processes using a variety of statistical distributions. Recent ecological SSMs are often complex, with a large number of parameters to estimate. Through a simulation study, we show that even simple linear Gaussian SSMs can suffer from parameter- and state-estimation problems. We demonstrate that these problems occur primarily when measurement error is larger than biological stochasticity, the condition that often drives ecologists to use SSMs. Using an animal movement example, we show how these estimation problems can affect ecological inference. Biased parameter estimates of a SSM describing the movement of polar bears (Ursus maritimus) result in overestimating their energy expenditure. We suggest potential solutions, but show that it often remains difficult to estimate parameters. While SSMs are powerful tools, they can give misleading results and we urge ecologists to assess whether the parameters can be estimated accurately before drawing ecological conclusions from their results.
Auger-Méthé, Marie; Field, Chris; Albertsen, Christoffer M.; Derocher, Andrew E.; Lewis, Mark A.; Jonsen, Ian D.; Mills Flemming, Joanna
2016-01-01
State-space models (SSMs) are increasingly used in ecology to model time-series such as animal movement paths and population dynamics. This type of hierarchical model is often structured to account for two levels of variability: biological stochasticity and measurement error. SSMs are flexible. They can model linear and nonlinear processes using a variety of statistical distributions. Recent ecological SSMs are often complex, with a large number of parameters to estimate. Through a simulation study, we show that even simple linear Gaussian SSMs can suffer from parameter- and state-estimation problems. We demonstrate that these problems occur primarily when measurement error is larger than biological stochasticity, the condition that often drives ecologists to use SSMs. Using an animal movement example, we show how these estimation problems can affect ecological inference. Biased parameter estimates of a SSM describing the movement of polar bears (Ursus maritimus) result in overestimating their energy expenditure. We suggest potential solutions, but show that it often remains difficult to estimate parameters. While SSMs are powerful tools, they can give misleading results and we urge ecologists to assess whether the parameters can be estimated accurately before drawing ecological conclusions from their results. PMID:27220686
NASA Astrophysics Data System (ADS)
Frick, K.; Grasmair, M.
2012-10-01
We study the application of the augmented Lagrangian method to the solution of linear ill-posed problems. Previously, linear convergence rates with respect to the Bregman distance have been derived under the classical assumption of a standard source condition. Using the method of variational inequalities, we extend these results in this paper to convergence rates of lower order, both for the case of an a priori parameter choice and an a posteriori choice based on Morozov’s discrepancy principle. In addition, our approach allows the derivation of convergence rates with respect to distance measures different from the Bregman distance. As a particular application, we consider sparsity promoting regularization, where we derive a range of convergence rates with respect to the norm under the assumption of restricted injectivity in conjunction with generalized source conditions of Hölder type.
Resampling versus repair in evolution strategies applied to a constrained linear problem.
Arnold, Dirk V
2013-01-01
We study the behaviour of multi-recombination evolution strategies for the problem of maximising a linear function with a single linear constraint. Two variants of the algorithm are considered: a strategy that resamples infeasible candidate solutions and one that applies a simple repair mechanism. Integral expressions that describe the strategies' one-generation behaviour are derived and used in a simple zeroth order model for the steady state attained when operating with constant step size. Applied to the analysis of cumulative step size adaptation, the approach provides an intuitive explanation for the qualitative difference in the algorithm variants' behaviour. The findings have implications for the design of constraint handling techniques to be used in connection with cumulative step size adaptation.
Robustness in linear quadratic feedback design with application to an aircraft control problem
NASA Technical Reports Server (NTRS)
Patel, R. V.; Sridhar, B.; Toda, M.
1977-01-01
Some new results concerning robustness and asymptotic properties of error bounds of a linear quadratic feedback design are applied to an aircraft control problem. An autopilot for the flare control of the Augmentor Wing Jet STOL Research Aircraft (AWJSRA) is designed based on Linear Quadratic (LQ) theory and the results developed in this paper. The variation of the error bounds to changes in the weighting matrices in the LQ design is studied by computer simulations, and appropriate weighting matrices are chosen to obtain a reasonable error bound for variations in the system matrix and at the same time meet the practical constraints for the flare maneuver of the AWJSRA. Results from the computer simulation of a satisfactory autopilot design for the flare control of the AWJSRA are presented.
A method of fast, sequential experimental design for linearized geophysical inverse problems
NASA Astrophysics Data System (ADS)
Coles, Darrell A.; Morgan, Frank Dale
2009-07-01
An algorithm for linear(ized) experimental design is developed for a determinant-based design objective function. This objective function is common in design theory and is used to design experiments that minimize the model entropy, a measure of posterior model uncertainty. Of primary significance in design problems is computational expediency. Several earlier papers have focused attention on posing design objective functions and opted to use global search methods for finding the critical points of these functions, but these algorithms are too slow to be practical. The proposed technique is distinguished primarily for its computational efficiency, which derives partly from a greedy optimization approach, termed sequential design. Computational efficiency is further enhanced through formulae for updating determinants and matrix inverses without need for direct calculation. The design approach is orders of magnitude faster than a genetic algorithm applied to the same design problem. However, greedy optimization often trades global optimality for increased computational speed; the ramifications of this tradeoff are discussed. The design methodology is demonstrated on a simple, single-borehole DC electrical resistivity problem. Designed surveys are compared with random and standard surveys, both with and without prior information. All surveys were compared with respect to a `relative quality' measure, the post-inversion model per cent rms error. The issue of design for inherently ill-posed inverse problems is considered and an approach for circumventing such problems is proposed. The design algorithm is also applied in an adaptive manner, with excellent results suggesting that smart, compact experiments can be designed in real time.
ERIC Educational Resources Information Center
Vice President's Task Force on Youth Employment, Washington, DC.
This series of nine reports reviews available information on the special needs and concentrated problems of youth employment. (It constitutes the second of a three-volume compendium; other volumes examine causes and dimensions of youth employment problems and analyze program experience--see note.) The effects of discrimination on minority youth…
ERIC Educational Resources Information Center
Shure, Myrna B.
Designed for teachers of kindergarten and the primary grades to enable children to learn how to solve the problems they have with others, the underlying goal of the program is to help children develop problem-solving skills so that they learn how to think, not what to think. The 89 lessons are adaptable for various levels of ability throughout the…
I Can Problem Solve: An Interpersonal Cognitive Problem-Solving Program. Preschool.
ERIC Educational Resources Information Center
Shure, Myrna B.
Designed for teachers of preschool to enable children to learn how to solve the problems they have with others, the underlying goal of the program is to help children develop problem-solving skills so that they learn how to think, not what to think. Originally developed for four-year-old children in a preschool setting, most three-year-old…
Using Perturbed QR Factorizations To Solve Linear Least-Squares Problems
Avron, Haim; Ng, Esmond G.; Toledo, Sivan
2008-03-21
We propose and analyze a new tool to help solve sparse linear least-squares problems min{sub x} {parallel}Ax-b{parallel}{sub 2}. Our method is based on a sparse QR factorization of a low-rank perturbation {cflx A} of A. More precisely, we show that the R factor of {cflx A} is an effective preconditioner for the least-squares problem min{sub x} {parallel}Ax-b{parallel}{sub 2}, when solved using LSQR. We propose applications for the new technique. When A is rank deficient we can add rows to ensure that the preconditioner is well-conditioned without column pivoting. When A is sparse except for a few dense rows we can drop these dense rows from A to obtain {cflx A}. Another application is solving an updated or downdated problem. If R is a good preconditioner for the original problem A, it is a good preconditioner for the updated/downdated problem {cflx A}. We can also solve what-if scenarios, where we want to find the solution if a column of the original matrix is changed/removed. We present a spectral theory that analyzes the generalized spectrum of the pencil (A*A,R*R) and analyze the applications.
Sixth SIAM conference on applied linear algebra: Final program and abstracts. Final technical report
1997-12-31
Linear algebra plays a central role in mathematics and applications. The analysis and solution of problems from an amazingly wide variety of disciplines depend on the theory and computational techniques of linear algebra. In turn, the diversity of disciplines depending on linear algebra also serves to focus and shape its development. Some problems have special properties (numerical, structural) that can be exploited. Some are simply so large that conventional approaches are impractical. New computer architectures motivate new algorithms, and fresh ways to look at old ones. The pervasive nature of linear algebra in analyzing and solving problems means that people from a wide spectrum--universities, industrial and government laboratories, financial institutions, and many others--share an interest in current developments in linear algebra. This conference aims to bring them together for their mutual benefit. Abstracts of papers presented are included.
Complexity and Computability of Solutions to Linear Programming Systems.
1980-02-01
any purpose of the United States Government. .. ix CENTER FOR CYBERNETIC STUDIES A. Charnes, Director Business - Economics Building, 203E 4 .The...Balinski and R.E. Gomory, "A Primal Method for the Assignment and Transportation Problems," Management Science , 10, 578-594, (1964). 3. A. Ben-Israel...School of Business Administration This research was partly supported by Project NR047-071, ONR Contract N00014-80-C-0242, and Project NR047-021, ONR
Fredholm alternative for periodic-Dirichlet problems for linear hyperbolic systems
NASA Astrophysics Data System (ADS)
Kmit, Irina; Recke, Lutz
2007-11-01
This paper concerns hyperbolic systems of two linear first-order PDEs in one space dimension with periodicity conditions in time and reflection boundary conditions in space. The coefficients of the PDEs are supposed to be time independent, but allowed to be discontinuous with respect to the space variable. We construct two scales of Banach spaces (for the solutions and for the right-hand sides of the equations, respectively) such that the problem can be modeled by means of Fredholm operators of index zero between corresponding spaces of the two scales.
On the classical solution to the linear-constrained minimum energy problem
NASA Astrophysics Data System (ADS)
Boissaux, Marc; Schiltz, Jang
2012-02-01
Minimum energy problems involving linear systems with quadratic performance criteria are classical in optimal control theory. The case where controls are constrained is discussed in Athans and Falb (1966) [Athans, M. and Falb, P.L. (1966), Optimal Control: An Introduction to the Theory and Its Applications, New York: McGraw-Hill Book Co.] who obtain a componentwise optimal control expression involving a saturation function expression. We show why the given expression is not generally optimal in the case where the dimension of the control is greater than one and provide a numerical counterexample.
NASA Astrophysics Data System (ADS)
Wu, Jiming; Gao, Zhiming; Dai, Zihuan
2012-08-01
In this paper a stabilized discretization scheme for the heterogeneous and anisotropic diffusion problems is proposed on general, possibly nonconforming polygonal meshes. The unknowns are the values at the cell center and the scheme relies on linearity-preserving criterion and the use of the so-called harmonic averaging points located at the interface of heterogeneity. The stability result and error estimate both in H1 norm are obtained under quite general and standard assumptions on polygonal meshes. The experiment results on a number of different meshes show that the scheme maintains optimal convergence rates in both L2 and H1 norms.
Parallel solution of sparse one-dimensional dynamic programming problems
NASA Technical Reports Server (NTRS)
Nicol, David M.
1989-01-01
Parallel computation offers the potential for quickly solving large computational problems. However, it is often a non-trivial task to effectively use parallel computers. Solution methods must sometimes be reformulated to exploit parallelism; the reformulations are often more complex than their slower serial counterparts. We illustrate these points by studying the parallelization of sparse one-dimensional dynamic programming problems, those which do not obviously admit substantial parallelization. We propose a new method for parallelizing such problems, develop analytic models which help us to identify problems which parallelize well, and compare the performance of our algorithm with existing algorithms on a multiprocessor.
Solving Classification Problems Using Genetic Programming Algorithms on GPUs
NASA Astrophysics Data System (ADS)
Cano, Alberto; Zafra, Amelia; Ventura, Sebastián
Genetic Programming is very efficient in problem solving compared to other proposals but its performance is very slow when the size of the data increases. This paper proposes a model for multi-threaded Genetic Programming classification evaluation using a NVIDIA CUDA GPUs programming model to parallelize the evaluation phase and reduce computational time. Three different well-known Genetic Programming classification algorithms are evaluated using the parallel evaluation model proposed. Experimental results using UCI Machine Learning data sets compare the performance of the three classification algorithms in single and multithreaded Java, C and CUDA GPU code. Results show that our proposal is much more efficient.
Baran, Richard; Northen, Trent R
2013-10-15
Untargeted metabolite profiling using liquid chromatography and mass spectrometry coupled via electrospray ionization is a powerful tool for the discovery of novel natural products, metabolic capabilities, and biomarkers. However, the elucidation of the identities of uncharacterized metabolites from spectral features remains challenging. A critical step in the metabolite identification workflow is the assignment of redundant spectral features (adducts, fragments, multimers) and calculation of the underlying chemical formula. Inspection of the data by experts using computational tools solving partial problems (e.g., chemical formula calculation for individual ions) can be performed to disambiguate alternative solutions and provide reliable results. However, manual curation is tedious and not readily scalable or standardized. Here we describe an automated procedure for the robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming optimization (RAMSI). Chemical rules among related ions are expressed as linear constraints and both the spectra interpretation and chemical formula calculation are performed in a single optimization step. This approach is unbiased in that it does not require predefined sets of neutral losses and positive and negative polarity spectra can be combined in a single optimization. The procedure was evaluated with 30 experimental mass spectra and was found to effectively identify the protonated or deprotonated molecule ([M + H](+) or [M - H](-)) while being robust to the presence of background ions. RAMSI provides a much-needed standardized tool for interpreting ions for subsequent identification in untargeted metabolomics workflows.
User's manual for interfacing a leading edge, vortex rollup program with two linear panel methods
NASA Technical Reports Server (NTRS)
Desilva, B. M. E.; Medan, R. T.
1979-01-01
Sufficient instructions are provided for interfacing the Mangler-Smith, leading edge vortex rollup program with a vortex lattice (POTFAN) method and an advanced higher order, singularity linear analysis for computing the vortex effects for simple canard wing combinations.
A Vector Study of Linearized Supersonic Flow Applications to Nonplanar Problems
NASA Technical Reports Server (NTRS)
Martin, John C
1953-01-01
A vector study of the partial-differential equation of steady linearized supersonic flow is presented. General expressions which relate the velocity potential in the stream to the conditions on the disturbing surfaces, are derived. In connection with these general expressions the concept of the finite part of an integral is discussed. A discussion of problems dealing with planar bodies is given and the conditions for the solution to be unique are investigated. Problems concerning nonplanar systems are investigated, and methods are derived for the solution of some simple nonplanar bodies. The surface pressure distribution and the damping in roll are found for rolling tails consisting of four, six, and eight rectangular fins for the Mach number range where the region of interference between adjacent fins does not affect the fin tips.
NASA Technical Reports Server (NTRS)
1979-01-01
The computer program Linear SCIDNT which evaluates rotorcraft stability and control coefficients from flight or wind tunnel test data is described. It implements the maximum likelihood method to maximize the likelihood function of the parameters based on measured input/output time histories. Linear SCIDNT may be applied to systems modeled by linear constant-coefficient differential equations. This restriction in scope allows the application of several analytical results which simplify the computation and improve its efficiency over the general nonlinear case.
The MARX Modulator Development Program for the International Linear Collider
Leyh, G.E.; /SLAC
2006-06-12
The ILC Marx Modulator Development Program at SLAC is working towards developing a full-scale ILC Marx ''Reference Design'' modulator prototype, with the goal of significantly reducing the size and cost of the ILC modulator while improving overall modulator efficiency and availability. The ILC Reference Design prototype will provide a proof-of-concept model to industry in advance of Phase II SBIR funding, and also allow operation of the new 10MW L-Band Klystron prototypes immediately upon their arrival at SLAC.
Mapping Efficient Numerical Methods to the Solution of Multiple Objective Linear Programs
1991-03-01
dependent upon the technology of solving related sy ems of linear equations. Gill, Murray and Wright have emphasized the importance of rank-1 up- dates to...Bibliography 1. Bazaraa, Mokhtar S., John J. Jarvis and Hanif D. Sherali. Linear Programming and Network Flows. 2nd ed New York: John Wiley ^ Sons, Inc., 1990. 2
Optimizing the Teaching-Learning Process Through a Linear Programming Model--Stage Increment Model.
ERIC Educational Resources Information Center
Belgard, Maria R.; Min, Leo Yoon-Gee
An operations research method to optimize the teaching-learning process is introduced in this paper. In particular, a linear programing model is proposed which, unlike dynamic or control theory models, allows the computer to react to the responses of a learner in seconds or less. To satisfy the assumptions of linearity, the seemingly complicated…
NASA Technical Reports Server (NTRS)
Wiggins, R. A.
1972-01-01
The discrete general linear inverse problem reduces to a set of m equations in n unknowns. There is generally no unique solution, but we can find k linear combinations of parameters for which restraints are determined. The parameter combinations are given by the eigenvectors of the coefficient matrix. The number k is determined by the ratio of the standard deviations of the observations to the allowable standard deviations in the resulting solution. Various linear combinations of the eigenvectors can be used to determine parameter resolution and information distribution among the observations. Thus we can determine where information comes from among the observations and exactly how it constraints the set of possible models. The application of such analyses to surface-wave and free-oscillation observations indicates that (1) phase, group, and amplitude observations for any particular mode provide basically the same type of information about the model; (2) observations of overtones can enhance the resolution considerably; and (3) the degree of resolution has generally been overestimated for many model determinations made from surface waves.
Xia, Youshen; Sun, Changyin; Zheng, Wei Xing
2012-05-01
There is growing interest in solving linear L1 estimation problems for sparsity of the solution and robustness against non-Gaussian noise. This paper proposes a discrete-time neural network which can calculate large linear L1 estimation problems fast. The proposed neural network has a fixed computational step length and is proved to be globally convergent to an optimal solution. Then, the proposed neural network is efficiently applied to image restoration. Numerical results show that the proposed neural network is not only efficient in solving degenerate problems resulting from the nonunique solutions of the linear L1 estimation problems but also needs much less computational time than the related algorithms in solving both linear L1 estimation and image restoration problems.
A linear model approach for ultrasonic inverse problems with attenuation and dispersion.
Carcreff, Ewen; Bourguignon, Sébastien; Idier, Jérôme; Simon, Laurent
2014-07-01
Ultrasonic inverse problems such as spike train deconvolution, synthetic aperture focusing, or tomography attempt to reconstruct spatial properties of an object (discontinuities, delaminations, flaws, etc.) from noisy and incomplete measurements. They require an accurate description of the data acquisition process. Dealing with frequency-dependent attenuation and dispersion is therefore crucial because both phenomena modify the wave shape as the travel distance increases. In an inversion context, this paper proposes to exploit a linear model of ultrasonic data taking into account attenuation and dispersion. The propagation distance is discretized to build a finite set of radiation impulse responses. Attenuation is modeled with a frequency power law and then dispersion is computed to yield physically consistent responses. Using experimental data acquired from attenuative materials, this model outperforms the standard attenuation-free model and other models of the literature. Because of model linearity, robust estimation methods can be implemented. When matched filtering is employed for single echo detection, the model that we propose yields precise estimation of the attenuation coefficient and of the sound velocity. A thickness estimation problem is also addressed through spike deconvolution, for which the proposed model also achieves accurate results.
Linear stability of the Couette flow of a vibrationally excited gas. 2. viscous problem
NASA Astrophysics Data System (ADS)
Grigor'ev, Yu. N.; Ershov, I. V.
2016-03-01
Based on the linear theory, stability of viscous disturbances in a supersonic plane Couette flow of a vibrationally excited gas described by a system of linearized equations of two-temperature gas dynamics including shear and bulk viscosity is studied. It is demonstrated that two sets are identified in the spectrum of the problem of stability of plane waves, similar to the case of a perfect gas. One set consists of viscous acoustic modes, which asymptotically converge to even and odd inviscid acoustic modes at high Reynolds numbers. The eigenvalues from the other set have no asymptotic relationship with the inviscid problem and are characterized by large damping decrements. Two most unstable viscous acoustic modes (I and II) are identified; the limits of these modes were considered previously in the inviscid approximation. It is shown that there are domains in the space of parameters for both modes, where the presence of viscosity induces appreciable destabilization of the flow. Moreover, the growth rates of disturbances are appreciably greater than the corresponding values for the inviscid flow, while thermal excitation in the entire considered range of parameters increases the stability of the viscous flow. For a vibrationally excited gas, the critical Reynolds number as a function of the thermal nonequilibrium degree is found to be greater by 12% than for a perfect gas.
NASA Astrophysics Data System (ADS)
Singh, Vikas; Xu, Jinhui; Hoffmann, Kenneth R.; Noël, Peter B.; Walczak, Alan M.
2006-03-01
Multi-view imaging is the primary modality for high-spatial-resolution imaging of the vasculature. The 3D vascular structure can be reconstructed if the imaging geometries are determined using known corresponding point-pairs (or k-tuples) in two or more images. Because the accuracy improves with more input corresponding point-pairs, we propose a new technique to automatically determine corresponding point-pairs in multi-view (k-view) images, from 2D vessel image centerlines. We formulate the problem, first as a multi-partite graph-matching problem. Each 2D centerline point is a vertex; each individual graph contains all vessel-points (vertices) in an image. The weight ('cost') of the edges between vertices (in different graphs) is the shortest distance between the points' respective projection-lines. Using this construction, a universe of mappings (k-tuples) is created, each k-tuple having k vertices (one from each image). A k-tuple's weight is the sum of pair-wise 'costs' of its members. Ideally, a set of such mappings is desired that preserves the ordering of points along the vessel and minimizes an appropriate global cost function, such that all vertices (in all graphs) participate in at least one mapping. We formulate this problem as a special case of the well-studied Set-Cover problem with additional constraints. Then, the equivalent linear program is solved, and randomized-rounding techniques are used to yield a feasible set of mappings. Our algorithm is efficient and yields a theoretical quality guarantee. In simulations, the correct matching is achieved in ~98% cases, even with high input error. In clinical data, apparently correct matching is achieved in >90% cases. This method should provide the basis for improving the calculated 3D vasculature from multi-view data-sets.
ERIC Educational Resources Information Center
Smith, H. Gene; And Others
The report describes a project for developing a linear programing technique and a data base to facilitate decision making in State level planning of occupational training programs. The first 32 pages of the report describe the methods and procedures, results, conclusions, and recommendations of the study and include a brief bibliography. The…
Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang
2014-01-01
Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images
Using linear programming and geographical information systems (GIS) to model material reuse
Nobel, C.E.; Keckler, S.E.; Allen, D.T.
1998-12-31
A material reuse model that identifies cost-optimal reuse scenarios has been developed and applied to a water reuse planning problem. The model utilizes a linear programming algorithm within a Geographic Information Systems (GIS) map-based framework. Specifically, the model integrates database operations and optimization methods with the visualization benefits and geographic analysis offered by maps. The model was applied to water reuse planning because of the many possibilities for water reuse among a set of co-located facilities. The two steps of the water reuse modeling process are: determining the feasible reuse opportunities based on quality and solving a linear program to find the cost-based optimal scenario. This paper focuses on the development, formulation, and potential of this model. The model is illustrated through a case study of the Bayport Industrial Complex in Pasadena, Texas. The case study included an industrial water treatment plant, a wastewater treatment plant, and more than forty manufacturing facilities. For a set of three industries in the Bayport complex, potential cost savings of 11 percent and water savings of 82 percent were identified. For a set of eleven industries, cost savings of 18 percent and water savings of 76 percent were found. The cost included treatment, purchase price, and an water transportation cost based on distance. This model has applicability to water reclamation project planning as well as water management in water-poor regions. Additionally, with minor modifications, the water reuse model presented here may be used to quantitatively analyze the use and reuse of other materials. Thus, this model provides a quantitative tool to promote more efficient and sustainable system-based material cycles.
Mitsos, Alexander; Melas, Ioannis N; Morris, Melody K; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Alexopoulos, Leonidas G
2012-01-01
Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.
Morris, Melody K.; Saez-Rodriguez, Julio; Lauffenburger, Douglas A.; Alexopoulos, Leonidas G.
2012-01-01
Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms. PMID:23226239
Biomedical image analysis using Markov random fields & efficient linear programing.
Komodakis, Nikos; Besbes, Ahmed; Glocker, Ben; Paragios, Nikos
2009-01-01
Computer-aided diagnosis through biomedical image analysis is increasingly considered in health sciences. This is due to the progress made on the acquisition side, as well as on the processing one. In vivo visualization of human tissues where one can determine both anatomical and functional information is now possible. The use of these images with efficient intelligent mathematical and processing tools allows the interpretation of the tissues state and facilitates the task of the physicians. Segmentation and registration are the two most fundamental tools in bioimaging. The first aims to provide automatic tools for organ delineation from images, while the second focuses on establishing correspondences between observations inter and intra subject and modalities. In this paper, we present some recent results towards a common formulation addressing these problems, called the Markov Random Fields. Such an approach is modular with respect to the application context, can be easily extended to deal with various modalities, provides guarantees on the optimality properties of the obtained solution and is computationally efficient.
Optimized wavelet domain watermark embedding strategy using linear programming
NASA Astrophysics Data System (ADS)
Pereira, Shelby; Voloshynovskiy, Sviatoslav V.; Pun, Thierry
2000-04-01
Invisible Digital watermarks have been proposed as a method for discouraging illicit copying and distribution of copyright material. In recent years it has been recognized that embedding information in a transform domain leads to more robust watermarks. In particular, several approaches based on the wavelet transform have ben proposed to address the problem of image water marking. The advantage of the wavelet transform relative to the DFT or DCT is that it allows for localized water marking of the image. A major difficulty, however, in watermarking in any transform domain lies in the fact that constraints on the allowable distortion at any pixel are specified in the spatial domain. In order to insert an invisible watermark, the current trend has been to model the Human Visual Systems and specify a masking function which yields the allowable distortion for any pixel. This complex function combines contrast, luminance, color, texture and edges. The watermark is then inserted in the transform domain and the inverse transform computed. The watermark is finally adjusted to satisfy the constraints on the pixel distortions. However this method is highly suboptimal since it leads to irreversible losses at the embedding stage because the watermark is being adjusted in the spatial domain with no care for the consequences in the transform domain.
NASA Astrophysics Data System (ADS)
Zhou, Qinglong; Long, Yiming
2017-04-01
In this paper, we consider the elliptic collinear solutions of the classical n-body problem, where the n bodies always stay on a straight line, and each of them moves on its own elliptic orbit with the same eccentricity. Such a motion is called an elliptic Euler-Moulton collinear solution. Here we prove that the corresponding linearized Hamiltonian system at such an elliptic Euler-Moulton collinear solution of n-bodies splits into (n-1) independent linear Hamiltonian systems, the first one is the linearized Hamiltonian system of the Kepler 2-body problem at Kepler elliptic orbit, and each of the other (n-2) systems is the essential part of the linearized Hamiltonian system at an elliptic Euler collinear solution of a 3-body problem whose mass parameter is modified. Then the linear stability of such a solution in the n-body problem is reduced to those of the corresponding elliptic Euler collinear solutions of the 3-body problems, which for example then can be further understood using numerical results of Martínez et al. on 3-body Euler solutions in 2004-2006. As an example, we carry out the detailed derivation of the linear stability for an elliptic Euler-Moulton solution of the 4-body problem with two small masses in the middle.
Communications oriented programming of parallel iterative solutions of sparse linear systems
NASA Technical Reports Server (NTRS)
Patrick, M. L.; Pratt, T. W.
1986-01-01
Parallel algorithms are developed for a class of scientific computational problems by partitioning the problems into smaller problems which may be solved concurrently. The effectiveness of the resulting parallel solutions is determined by the amount and frequency of communication and synchronization and the extent to which communication can be overlapped with computation. Three different parallel algorithms for solving the same class of problems are presented, and their effectiveness is analyzed from this point of view. The algorithms are programmed using a new programming environment. Run-time statistics and experience obtained from the execution of these programs assist in measuring the effectiveness of these algorithms.
Linearized Programming of Memristors for Artificial Neuro-Sensor Signal Processing.
Yang, Changju; Kim, Hyongsuk
2016-08-19
A linearized programming method of memristor-based neural weights is proposed. Memristor is known as an ideal element to implement a neural synapse due to its embedded functions of analog memory and analog multiplication. Its resistance variation with a voltage input is generally a nonlinear function of time. Linearization of memristance variation about time is very important for the easiness of memristor programming. In this paper, a method utilizing an anti-serial architecture for linear programming is proposed. The anti-serial architecture is composed of two memristors with opposite polarities. It linearizes the variation of memristance due to complimentary actions of two memristors. For programming a memristor, additional memristor with opposite polarity is employed. The linearization effect of weight programming of an anti-serial architecture is investigated and memristor bridge synapse which is built with two sets of anti-serial memristor architecture is taken as an application example of the proposed method. Simulations are performed with memristors of both linear drift model and nonlinear model.
Linearized Programming of Memristors for Artificial Neuro-Sensor Signal Processing
Yang, Changju; Kim, Hyongsuk
2016-01-01
A linearized programming method of memristor-based neural weights is proposed. Memristor is known as an ideal element to implement a neural synapse due to its embedded functions of analog memory and analog multiplication. Its resistance variation with a voltage input is generally a nonlinear function of time. Linearization of memristance variation about time is very important for the easiness of memristor programming. In this paper, a method utilizing an anti-serial architecture for linear programming is proposed. The anti-serial architecture is composed of two memristors with opposite polarities. It linearizes the variation of memristance due to complimentary actions of two memristors. For programming a memristor, additional memristor with opposite polarity is employed. The linearization effect of weight programming of an anti-serial architecture is investigated and memristor bridge synapse which is built with two sets of anti-serial memristor architecture is taken as an application example of the proposed method. Simulations are performed with memristors of both linear drift model and nonlinear model. PMID:27548186
The Computer Program LIAR for Beam Dynamics Calculations in Linear Accelerators
Assmann, R.W.; Adolphsen, C.; Bane, K.; Raubenheimer, T.O.; Siemann, R.H.; Thompson, K.; /SLAC
2011-08-26
Linear accelerators are the central components of the proposed next generation of linear colliders. They need to provide acceleration of up to 750 GeV per beam while maintaining very small normalized emittances. Standard simulation programs, mainly developed for storage rings, do not meet the specific requirements for high energy linear accelerators. We present a new program LIAR ('LInear Accelerator Research code') that includes wakefield effects, a 6D coupled beam description, specific optimization algorithms and other advanced features. Its modular structure allows to use and to extend it easily for different purposes. The program is available for UNIX workstations and Windows PC's. It can be applied to a broad range of accelerators. We present examples of simulations for SLC and NLC.
Managing problem employees: a model program and practical guide.
Miller, Laurence
2010-01-01
This article presents a model program for managing problem employees that includes a description ofthe basic types of problem employees and employee problems, as well as practical recommendations for. (1) selection and screening, (2) education and training, (3) coaching and counseling, (4) discipline, (5) psychological fitness-for-duty evaluations, (6) mental health services, (7) termination, and (8) leadership and administrative strategies. Throughout, the emphasis on balancing the need for order and productivity in the workplace with fairness and concern for employee health and well-being.
NASA Astrophysics Data System (ADS)
Zhang, Chenglong; Guo, Ping
2017-10-01
The vague and fuzzy parametric information is a challenging issue in irrigation water management problems. In response to this problem, a generalized fuzzy credibility-constrained linear fractional programming (GFCCFP) model is developed for optimal irrigation water allocation under uncertainty. The model can be derived from integrating generalized fuzzy credibility-constrained programming (GFCCP) into a linear fractional programming (LFP) optimization framework. Therefore, it can solve ratio optimization problems associated with fuzzy parameters, and examine the variation of results under different credibility levels and weight coefficients of possibility and necessary. It has advantages in: (1) balancing the economic and resources objectives directly; (2) analyzing system efficiency; (3) generating more flexible decision solutions by giving different credibility levels and weight coefficients of possibility and (4) supporting in-depth analysis of the interrelationships among system efficiency, credibility level and weight coefficient. The model is applied to a case study of irrigation water allocation in the middle reaches of Heihe River Basin, northwest China. Therefore, optimal irrigation water allocation solutions from the GFCCFP model can be obtained. Moreover, factorial analysis on the two parameters (i.e. λ and γ) indicates that the weight coefficient is a main factor compared with credibility level for system efficiency. These results can be effective for support reasonable irrigation water resources management and agricultural production.
Linear stability analysis in the numerical solution of initial value problems
NASA Astrophysics Data System (ADS)
van Dorsselaer, J. L. M.; Kraaijevanger, J. F. B. M.; Spijker, M. N.
This article addresses the general problem of establishing upper bounds for the norms of the nth powers of square matrices. The focus is on upper bounds that grow only moderately (or stay constant) where n, or the order of the matrices, increases. The so-called resolvant condition, occuring in the famous Kreiss matrix theorem, is a classical tool for deriving such bounds.Recently the classical upper bounds known to be valid under Kreiss's resolvant condition have been improved. Moreover, generalizations of this resolvant condition have been considered so as to widen the range of applications. The main purpose of this article is to review and extend some of these new developments.The upper bounds for the powers of matrices discussed in this article are intimately connected with the stability analysis of numerical processes for solving initial(-boundary) value problems in ordinary and partial linear differential equations. The article highlights this connection.The article concludes with numerical illustrations in the solution of a simple initial-boundary value problem for a partial differential equation.
Linear problem of the shock wave disturbance in a non-classical case
NASA Astrophysics Data System (ADS)
Semenko, Evgeny V.
2017-06-01
A linear problem of the shock wave disturbance for a special (non-classical) case, where both pre-shock and post-shock flows are subsonic, is considered. The phase transition for the van der Waals gas is an example of this problem. Isentropic solutions are constructed. In addition, the stability of the problem is investigated and the known result is approved: the only neutral stability case occurs here. A strictly algebraic representation of the solution in the plane of the Fourier transform is obtained. This representation allows the solution to be studied both analytically and numerically. In this way, any solution can be decomposed into a sum of acoustic and vorticity waves and into a sum of initial (generated by initial perturbations), transmitted (through the shock) and reflected (from the shock) waves. Thus, the wave incidence/refraction/reflection is investigated. A principal difference of the refraction/reflection from the classical case is found, namely, the waves generated by initial pre-shock perturbations not only pass through the shock (i.e., generate post-shock transmitted waves) but also are reflected from it (i.e., generate pre-shock reflected waves). In turn, the waves generated by the initial post-shock perturbation are not only reflected from the shock (generate post-shock reflected waves) but also pass through it (generate pre-shock transmitted waves).
Quantum algorithms for the ordered search problem via semidefinite programming
Childs, Andrew M.; Landahl, Andrew J.; Parrilo, Pablo A.
2007-03-15
One of the most basic computational problems is the task of finding a desired item in an ordered list of N items. While the best classical algorithm for this problem uses log{sub 2} N queries to the list, a quantum computer can solve the problem using a constant factor fewer queries. However, the precise value of this constant is unknown. By characterizing a class of quantum query algorithms for the ordered search problem in terms of a semidefinite program, we find quantum algorithms for small instances of the ordered search problem. Extending these algorithms to arbitrarily large instances using recursion, we show that there is an exact quantum ordered search algorithm using 4 log{sub 605} N{approx_equal}0.433 log{sub 2} N queries, which improves upon the previously best known exact algorithm.
NASA Astrophysics Data System (ADS)
Dotti, Gustavo; Gleiser, Reinaldo J.
2009-11-01
The coupled equations for the scalar modes of the linearized Einstein equations around Schwarzschild's spacetime were reduced by Zerilli to a (1+1) wave equation \\partial ^2 \\Psi _z / \\partial t^2 + {\\cal H} \\Psi _z =0 , where {\\cal H} = -\\partial ^2 / \\partial x^2 + V(x) is the Zerilli 'Hamiltonian' and x is the tortoise radial coordinate. From its definition, for smooth metric perturbations the field Ψz is singular at rs = -6M/(ell - 1)(ell +2), with ell being the mode harmonic number. The equation Ψz obeys is also singular, since V has a second-order pole at rs. This is irrelevant to the black hole exterior stability problem, where r > 2M > 0, and rs < 0, but it introduces a non-trivial problem in the naked singular case where M < 0, then rs > 0, and the singularity appears in the relevant range of r (0 < r < ∞). We solve this problem by developing a new approach to the evolution of the even mode, based on a new gauge invariant function, \\hat{\\Psi} , that is a regular function of the metric perturbation for any value of M. The relation of \\hat{\\Psi} to Ψz is provided by an intertwiner operator. The spatial pieces of the (1 + 1) wave equations that \\hat{\\Psi} and Ψz obey are related as a supersymmetric pair of quantum Hamiltonians {\\cal H} and \\hat{\\cal H} . For M<0, \\hat{\\cal H} has a regular potential and a unique self-adjoint extension in a domain {\\cal D} defined by a physically motivated boundary condition at r = 0. This allows us to address the issue of evolution of gravitational perturbations in this non-globally hyperbolic background. This formulation is used to complete the proof of the linear instability of the Schwarzschild naked singularity, by showing that a previously found unstable mode belongs to a complete basis of \\hat{\\cal H} in {\\cal D} , and thus is excitable by generic initial data. This is further illustrated by numerically solving the linearized equations for suitably chosen initial data.
EARLY DETECTION AND PROGRAMING FOR CHILDREN WITH SCHOOL ADJUSTMENT PROBLEMS.
ERIC Educational Resources Information Center
MCGAHAN, F.E.
THE GALENA PARK SPECIAL PROGRAM IS AN EFFORT ON THE PART OF THE SCHOOL ADMINISTRATION TO DETECT, AT THE EARLIEST TIME, ANY STUDENT PROBLEM WHICH MAY LEAD TO DIFFICULTIES IN SCHOOL ADJUSTMENT. ALL PHASES OF PUPIL PERSONNEL SERVICES ARE PLACED UNDER ONE COORDINATOR TO EXPEDITE SERVICES TO THE CHILD IN DIFFICULTY. EARLY DETECTION OF POTENTIAL PROBLEM…
Robust semidefinite programming approach to the separability problem
Brandao, Fernando G.S.L.; Vianna, Reinaldo O.
2004-12-01
We express the optimization of entanglement witnesses for arbitrary bipartite states in terms of a class of convex optimization problems known as robust semidefinite programs (RSDPs). We propose, using well known properties of RSDPs, several sufficient tests for separability of mixed states. Our results are then generalized to multipartite density operators.
Approximate proximal point methods for convex programming problems
Eggermont, P.
1994-12-31
We study proximal point methods for the finite dimensional convex programming problem minimize f(x) such that x {element_of} C, where f : dom f {contained_in} RIR is a proper convex function and C {contained_in} R is a closed convex set.
An Interdisciplinary Program in Technical Communications: Problems Encountered.
ERIC Educational Resources Information Center
Eckman, Martha
The need for experts in technical communication is growing significantly while the number of college graduates in the field accounts for less than one percent of the need. Three major types of problems should be considered in trying to establish a technical communication program: those involving society's need for better technical communicators,…
Parent Drug Education Programs: Reasons, Problems, and Implications.
ERIC Educational Resources Information Center
Fox, Tricia A.
1991-01-01
Presents an overview of parent drug education programs together with information regarding those problems, concerns, and needs faced by parents who are dealing with an offspring drug user/abuser. Emphasizes the unique, individual characteristics of parents and suggests that these influences may be the main determinants of the effectiveness of…