Problem solving with genetic algorithms and Splicer
NASA Technical Reports Server (NTRS)
Bayer, Steven E.; Wang, Lui
1991-01-01
Genetic algorithms are highly parallel, adaptive search procedures (i.e., problem-solving methods) loosely based on the processes of population genetics and Darwinian survival of the fittest. Genetic algorithms have proven useful in domains where other optimization techniques perform poorly. The main purpose of the paper is to discuss a NASA-sponsored software development project to develop a general-purpose tool for using genetic algorithms. The tool, called Splicer, can be used to solve a wide variety of optimization problems and is currently available from NASA and COSMIC. This discussion is preceded by an introduction to basic genetic algorithm concepts and a discussion of genetic algorithm applications.
Solving SAT Problem Based on Hybrid Differential Evolution Algorithm
NASA Astrophysics Data System (ADS)
Liu, Kunqi; Zhang, Jingmin; Liu, Gang; Kang, Lishan
Satisfiability (SAT) problem is an NP-complete problem. Based on the analysis about it, SAT problem is translated equally into an optimization problem on the minimum of objective function. A hybrid differential evolution algorithm is proposed to solve the Satisfiability problem. It makes full use of strong local search capacity of hill-climbing algorithm and strong global search capability of differential evolution algorithm, which makes up their disadvantages, improves the efficiency of algorithm and avoids the stagnation phenomenon. The experiment results show that the hybrid algorithm is efficient in solving SAT problem.
Using a genetic algorithm to solve fluid-flow problems
Pryor, R.J. )
1990-06-01
Genetic algorithms are based on the mechanics of the natural selection and natural genetics processes. These algorithms are finding increasing application to a wide variety of engineering optimization and machine learning problems. In this paper, the authors demonstrate the use of a genetic algorithm to solve fluid flow problems. Specifically, the authors use the algorithm to solve the one-dimensional flow equations for a pipe.
Problem Solving Techniques for the Design of Algorithms.
ERIC Educational Resources Information Center
Kant, Elaine; Newell, Allen
1984-01-01
Presents model of algorithm design (activity in software development) based on analysis of protocols of two subjects designing three convex hull algorithms. Automation methods, methods for studying algorithm design, role of discovery in problem solving, and comparison of different designs of case study according to model are highlighted.…
Artificial Bee Colony Algorithm for Solving Optimal Power Flow Problem
Le Dinh, Luong; Vo Ngoc, Dieu
2013-01-01
This paper proposes an artificial bee colony (ABC) algorithm for solving optimal power flow (OPF) problem. The objective of the OPF problem is to minimize total cost of thermal units while satisfying the unit and system constraints such as generator capacity limits, power balance, line flow limits, bus voltages limits, and transformer tap settings limits. The ABC algorithm is an optimization method inspired from the foraging behavior of honey bees. The proposed algorithm has been tested on the IEEE 30-bus, 57-bus, and 118-bus systems. The numerical results have indicated that the proposed algorithm can find high quality solution for the problem in a fast manner via the result comparisons with other methods in the literature. Therefore, the proposed ABC algorithm can be a favorable method for solving the OPF problem. PMID:24470790
Artificial bee colony algorithm for solving optimal power flow problem.
Le Dinh, Luong; Vo Ngoc, Dieu; Vasant, Pandian
2013-01-01
This paper proposes an artificial bee colony (ABC) algorithm for solving optimal power flow (OPF) problem. The objective of the OPF problem is to minimize total cost of thermal units while satisfying the unit and system constraints such as generator capacity limits, power balance, line flow limits, bus voltages limits, and transformer tap settings limits. The ABC algorithm is an optimization method inspired from the foraging behavior of honey bees. The proposed algorithm has been tested on the IEEE 30-bus, 57-bus, and 118-bus systems. The numerical results have indicated that the proposed algorithm can find high quality solution for the problem in a fast manner via the result comparisons with other methods in the literature. Therefore, the proposed ABC algorithm can be a favorable method for solving the OPF problem. PMID:24470790
Gradient Symplectic Algorithms for Solving Quantum Dynamical Problems
NASA Astrophysics Data System (ADS)
Chin, Siu A.; Chen, C. R.; Auer, J.; Krotscheck, E.
2002-03-01
Recent advances[1] in factorizing the classical and quantum evolution operator to fourth order with purely positive coefficients have produce a new class of Monte Carlo[2,3] and quantum dynamical algorithms[4,5] that are at least two orders of magnitude better than existing algorithms of comparble order. This talk will focus on solving the Schrodinger equation in real and imaginary time for the extraction of dynamical information and for the determination of eigenvalue-function pairs from large 3-D grids. References: [1]S. A. Chin, ``Symplectic Integrators From Composite Operator Factorizations" Phys. Lett. A226, 344 (1997). [2]H. A. Forbert and S. A. Chin ``Fourth-order algorithms for solving the multivariable Langevin equation and the Kramers equation", Phys. Rev. E63, 016703 (2001). [3]H. A. Forbert and S. A. Chin, ``Fourth-order diffusion Monte Carlo algorithms for solving quantum many-body problems", Phys. Rev. B63, 144518 (2001). [4]S. A. Chin and C. R. Chen, ``Fourth order gradient symplectic integrator methods for solving the time-dependent Schrodinger equation", J. Chem. Phys. 114, 7338 (2001). [5]J. Auer, E. Krotscheck, and S. A. Chin, ``A fourth-order real-space algorithm for solving local Schrodinger equations", J. Chem. Phys. 115, 6841 (2001).
Solving a multistage partial inspection problem using genetic algorithms
Heredia-Langner, Alejandro ); Montgomery, D C.; Carlyle, W M.
2002-01-01
Traditionally, the multistage inspection problem has been formulated as consisting of a decision schedule where some manufacturing stages receive full inspection and the rest none. Dynamic programming and heuristic methods (like local search) are the most commonly used solution techniques. A highly constrained multistage inspection problem is presented where all stages must receive partial rectifying inspection and it is solved using a real-valued genetic algorithm. This solution technique can handle multiple objectives and quality constraints effectively.
High-Performance Algorithm for Solving the Diagnosis Problem
NASA Technical Reports Server (NTRS)
Fijany, Amir; Vatan, Farrokh
2009-01-01
for IP to solve the diagnosis problem. In the IP approach, the diagnosis problem can be formulated as a linear integer optimization problem, which can be solved by use of well-developed integer-programming algorithms. This concludes the background information.
A domain decomposition algorithm for solving large elliptic problems
Nolan, M.P.
1991-01-01
AN algorithm which efficiently solves large systems of equations arising from the discretization of a single second-order elliptic partial differential equation is discussed. The global domain is partitioned into not necessarily disjoint subdomains which are traversed using the Schwarz Alternating Procedure. On each subdomain the multigrid method is used to advance the solution. The algorithm has the potential to decrease solution time when data is stored across multiple levels of a memory hierarchy. Results are presented for a virtual memory, vector multiprocessor architecture. A study of choice of inner iteration procedure and subdomain overlap is presented for a model problem, solved with two and four subdomains, sequentially and in parallel. Microtasking multiprocessing results are reported for multigrid on the Alliant FX-8 vector-multiprocessor. A convergence proof for a class of matrix splittings for the two-dimensional Helmholtz equation is given. 70 refs., 3 figs., 20 tabs.
ERIC Educational Resources Information Center
Mason, Diana S.; Shell, Duane F.; Crawley, Frank E.
1997-01-01
Identifies and describes the differences in the problem-solving methods used by faculty teaching introductory chemistry and students enrolled in an introductory chemistry course. Results indicate that students correctly solve algorithmic-mode problems more frequently. Contains 33 references. (DDR)
General heuristics algorithms for solving capacitated arc routing problem
NASA Astrophysics Data System (ADS)
Fadzli, Mohammad; Najwa, Nurul; Masran, Hafiz
2015-05-01
In this paper, we try to determine the near-optimum solution for the capacitated arc routing problem (CARP). In general, NP-hard CARP is a special graph theory specifically arises from street services such as residential waste collection and road maintenance. By purpose, the design of the CARP model and its solution techniques is to find optimum (or near-optimum) routing cost for a fleet of vehicles involved in operation. In other words, finding minimum-cost routing is compulsory in order to reduce overall operation cost that related with vehicles. In this article, we provide a combination of various heuristics algorithm to solve a real case of CARP in waste collection and benchmark instances. These heuristics work as a central engine in finding initial solutions or near-optimum in search space without violating the pre-setting constraints. The results clearly show that these heuristics algorithms could provide good initial solutions in both real-life and benchmark instances.
An amoeboid algorithm for solving linear transportation problem
NASA Astrophysics Data System (ADS)
Gao, Cai; Yan, Chao; Zhang, Zili; Hu, Yong; Mahadevan, Sankaran; Deng, Yong
2014-03-01
Transportation Problem (TP) is one of the basic operational research problems, which plays an important role in many practical applications. In this paper, a bio-inspired mathematical model is proposed to handle the Linear Transportation Problem (LTP) in directed networks by modifying the original amoeba model Physarum Solver. Several examples are used to prove that the provided model can effectively solve Balanced Transportation Problem (BTP), Unbalanced Transportation Problem (UTP), especially the Generalized Transportation Problem (GTP), in a nondiscrete way.
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.
ERIC Educational Resources Information Center
de Leeuw, L.
Sixty-four fifth and sixth-grade pupils were taught number series extrapolation by either an algorithm, fully prescribed problem-solving method or a heuristic, less prescribed method. The trained problems were within categories of two degrees of complexity. There were 16 subjects in each cell of the 2 by 2 design used. Aptitude Treatment…
Solving the time dependent vehicle routing problem by metaheuristic algorithms
NASA Astrophysics Data System (ADS)
Johar, Farhana; Potts, Chris; Bennell, Julia
2015-02-01
The problem we consider in this study is Time Dependent Vehicle Routing Problem (TDVRP) which has been categorized as non-classical VRP. It is motivated by the fact that multinational companies are currently not only manufacturing the demanded products but also distributing them to the customer location. This implies an efficient synchronization of production and distribution activities. Hence, this study will look into the routing of vehicles which departs from the depot at varies time due to the variation in manufacturing process. We consider a single production line where demanded products are being process one at a time once orders have been received from the customers. It is assumed that order released from the production line will be loaded into scheduled vehicle which ready to be delivered. However, the delivery could only be done once all orders scheduled in the vehicle have been released from the production line. Therefore, there could be lateness on the delivery process from awaiting all customers' order of the route to be released. Our objective is to determine a schedule for vehicle routing that minimizes the solution cost including the travelling and tardiness cost. A mathematical formulation is developed to represent the problem and will be solved by two metaheuristics; Variable Neighborhood Search (VNS) and Tabu Search (TS). These algorithms will be coded in C ++ programming and run using 56's Solomon instances with some modification. The outcome of this experiment can be interpreted as the quality criteria of the different approximation methods. The comparison done shown that VNS gave the better results while consuming reasonable computational efforts.
Duan, Qian-Qian; Yang, Gen-Ke; Pan, Chang-Chun
2014-01-01
A hybrid optimization algorithm combining finite state method (FSM) and genetic algorithm (GA) is proposed to solve the crude oil scheduling problem. The FSM and GA are combined to take the advantage of each method and compensate deficiencies of individual methods. In the proposed algorithm, the finite state method makes up for the weakness of GA which is poor at local searching ability. The heuristic returned by the FSM can guide the GA algorithm towards good solutions. The idea behind this is that we can generate promising substructure or partial solution by using FSM. Furthermore, the FSM can guarantee that the entire solution space is uniformly covered. Therefore, the combination of the two algorithms has better global performance than the existing GA or FSM which is operated individually. Finally, a real-life crude oil scheduling problem from the literature is used for conducting simulation. The experimental results validate that the proposed method outperforms the state-of-art GA method. PMID:24772031
Modified cooperative immune algorithm for solving classification problems
NASA Astrophysics Data System (ADS)
Wójcik, Waldemar; Lytvynenko, Volodymyr; Smailova, Saule
2013-01-01
The way of the decision of a problem of classification by means of immune algorithm which is based on a principle of cooperation of antibodies of a population is offered. The formal description of structure of an antibody and ways of their association within the limits of a population in the computer network functioning as a unit is given. The way of an estimation of antibodies as elements of a network is considered. The basic phases of work of algorithm, such as are considered: growth of a network, a mutation of cells, compression of a network.
A hybrid cuckoo search algorithm with Nelder Mead method for solving global optimization problems.
Ali, Ahmed F; Tawhid, Mohamed A
2016-01-01
Cuckoo search algorithm is a promising metaheuristic population based method. It has been applied to solve many real life problems. In this paper, we propose a new cuckoo search algorithm by combining the cuckoo search algorithm with the Nelder-Mead method in order to solve the integer and minimax optimization problems. We call the proposed algorithm by hybrid cuckoo search and Nelder-Mead method (HCSNM). HCSNM starts the search by applying the standard cuckoo search for number of iterations then the best obtained solution is passing to the Nelder-Mead algorithm as an intensification process in order to accelerate the search and overcome the slow convergence of the standard cuckoo search algorithm. The proposed algorithm is balancing between the global exploration of the Cuckoo search algorithm and the deep exploitation of the Nelder-Mead method. We test HCSNM algorithm on seven integer programming problems and ten minimax problems and compare against eight algorithms for solving integer programming problems and seven algorithms for solving minimax problems. The experiments results show the efficiency of the proposed algorithm and its ability to solve integer and minimax optimization problems in reasonable time. PMID:27217988
An efficient algorithm for solving the gravity problem of finding a density in a horizontal layer
NASA Astrophysics Data System (ADS)
Akimova, Elena N.; Martyshko, Peter S.; Misilov, Vladimir E.; Kosivets, Rostislav A.
2016-06-01
An efficient algorithm for solving the inverse gravity problem of finding a variable density in a horizontal layer using gravitational data is constructed. After the discretization and approximation, the problem reduces to solving a system of linear algebraic equations. The idea of this algorithm is based on exploiting the block-Toeplitz structure of coefficients matrix. Utilizing this algorithm drastically reduces the memory usage, as well as the computation time. The algorithm was parallelized and implemented using the Uran supercomputer. A model problem with synthetic gravitational data was solved.
Ontological Problem-Solving Framework for Dynamically Configuring Sensor Systems and Algorithms
Qualls, Joseph; Russomanno, David J.
2011-01-01
The deployment of ubiquitous sensor systems and algorithms has led to many challenges, such as matching sensor systems to compatible algorithms which are capable of satisfying a task. Compounding the challenges is the lack of the requisite knowledge models needed to discover sensors and algorithms and to subsequently integrate their capabilities to satisfy a specific task. A novel ontological problem-solving framework has been designed to match sensors to compatible algorithms to form synthesized systems, which are capable of satisfying a task and then assigning the synthesized systems to high-level missions. The approach designed for the ontological problem-solving framework has been instantiated in the context of a persistence surveillance prototype environment, which includes profiling sensor systems and algorithms to demonstrate proof-of-concept principles. Even though the problem-solving approach was instantiated with profiling sensor systems and algorithms, the ontological framework may be useful with other heterogeneous sensing-system environments. PMID:22163793
Greedy heuristic algorithm for solving series of eee components classification problems*
NASA Astrophysics Data System (ADS)
Kazakovtsev, A. L.; Antamoshkin, A. N.; Fedosov, V. V.
2016-04-01
Algorithms based on using the agglomerative greedy heuristics demonstrate precise and stable results for clustering problems based on k- means and p-median models. Such algorithms are successfully implemented in the processes of production of specialized EEE components for using in space systems which include testing each EEE device and detection of homogeneous production batches of the EEE components based on results of the tests using p-median models. In this paper, authors propose a new version of the genetic algorithm with the greedy agglomerative heuristic which allows solving series of problems. Such algorithm is useful for solving the k-means and p-median clustering problems when the number of clusters is unknown. Computational experiments on real data show that the preciseness of the result decreases insignificantly in comparison with the initial genetic algorithm for solving a single problem.
Qualls, Joseph; Russomanno, David J.
2011-01-01
The lack of knowledge models to represent sensor systems, algorithms, and missions makes opportunistically discovering a synthesis of systems and algorithms that can satisfy high-level mission specifications impractical. A novel ontological problem-solving framework has been designed that leverages knowledge models describing sensors, algorithms, and high-level missions to facilitate automated inference of assigning systems to subtasks that may satisfy a given mission specification. To demonstrate the efficacy of the ontological problem-solving architecture, a family of persistence surveillance sensor systems and algorithms has been instantiated in a prototype environment to demonstrate the assignment of systems to subtasks of high-level missions. PMID:22164081
Salcedo-Sanz, S; Del Ser, J; Landa-Torres, I; Gil-López, S; Portilla-Figueras, J A
2014-01-01
This paper presents a novel bioinspired algorithm to tackle complex optimization problems: the coral reefs optimization (CRO) algorithm. The CRO algorithm artificially simulates a coral reef, where different corals (namely, solutions to the optimization problem considered) grow and reproduce in coral colonies, fighting by choking out other corals for space in the reef. This fight for space, along with the specific characteristics of the corals' reproduction, produces a robust metaheuristic algorithm shown to be powerful for solving hard optimization problems. In this research the CRO algorithm is tested in several continuous and discrete benchmark problems, as well as in practical application scenarios (i.e., optimum mobile network deployment and off-shore wind farm design). The obtained results confirm the excellent performance of the proposed algorithm and open line of research for further application of the algorithm to real-world problems. PMID:25147860
Salcedo-Sanz, S.; Del Ser, J.; Landa-Torres, I.; Gil-López, S.; Portilla-Figueras, J. A.
2014-01-01
This paper presents a novel bioinspired algorithm to tackle complex optimization problems: the coral reefs optimization (CRO) algorithm. The CRO algorithm artificially simulates a coral reef, where different corals (namely, solutions to the optimization problem considered) grow and reproduce in coral colonies, fighting by choking out other corals for space in the reef. This fight for space, along with the specific characteristics of the corals' reproduction, produces a robust metaheuristic algorithm shown to be powerful for solving hard optimization problems. In this research the CRO algorithm is tested in several continuous and discrete benchmark problems, as well as in practical application scenarios (i.e., optimum mobile network deployment and off-shore wind farm design). The obtained results confirm the excellent performance of the proposed algorithm and open line of research for further application of the algorithm to real-world problems. PMID:25147860
Application of the artificial bee colony algorithm for solving the set covering problem.
Crawford, Broderick; Soto, Ricardo; Cuesta, Rodrigo; Paredes, Fernando
2014-01-01
The set covering problem is a formal model for many practical optimization problems. In the set covering problem the goal is to choose a subset of the columns of minimal cost that covers every row. Here, we present a novel application of the artificial bee colony algorithm to solve the non-unicost set covering problem. The artificial bee colony algorithm is a recent swarm metaheuristic technique based on the intelligent foraging behavior of honey bees. Experimental results show that our artificial bee colony algorithm is competitive in terms of solution quality with other recent metaheuristic approaches for the set covering problem. PMID:24883356
Neural Networks Art: Solving Problems with Multiple Solutions and New Teaching Algorithm
Dmitrienko, V. D; Zakovorotnyi, A. Yu.; Leonov, S. Yu.; Khavina, I. P
2014-01-01
A new discrete neural networks adaptive resonance theory (ART), which allows solving problems with multiple solutions, is developed. New algorithms neural networks teaching ART to prevent degradation and reproduction classes at training noisy input data is developed. Proposed learning algorithms discrete ART networks, allowing obtaining different classification methods of input. PMID:25246988
NASA Astrophysics Data System (ADS)
Marwati, Rini; Yulianti, Kartika; Pangestu, Herny Wulandari
2016-02-01
A fuzzy evolutionary algorithm is an integration of an evolutionary algorithm and a fuzzy system. In this paper, we present an application of a genetic algorithm to a fuzzy evolutionary algorithm to detect and to solve chromosomes conflict. A chromosome conflict is identified by existence of any two genes in a chromosome that has the same values as two genes in another chromosome. Based on this approach, we construct an algorithm to solve a lecture scheduling problem. Time codes, lecture codes, lecturer codes, and room codes are defined as genes. They are collected to become chromosomes. As a result, the conflicted schedule turns into chromosomes conflict. Built in the Delphi program, results show that the conflicted lecture schedule problem is solvable by this algorithm.
Tracking Problem Solving by Multivariate Pattern Analysis and Hidden Markov Model Algorithms
Anderson, John R.
2011-01-01
Multivariate pattern analysis can be combined with hidden Markov model algorithms to track the second-by-second thinking as people solve complex problems. Two applications of this methodology are illustrated with a data set taken from children as they interacted with an intelligent tutoring system for algebra. The first “mind reading” application involves using fMRI activity to track what students are doing as they solve a sequence of algebra problems. The methodology achieves considerable accuracy at determining both what problem-solving step the students are taking and whether they are performing that step correctly. The second “model discovery” application involves using statistical model evaluation to determine how many substates are involved in performing a step of algebraic problem solving. This research indicates that different steps involve different numbers of substates and these substates are associated with different fluency in algebra problem solving. PMID:21820455
ERIC Educational Resources Information Center
Mason, Diana; Crawley, Frank E.
The purpose of this investigation was to identify and describe the differences in the methods used by experts (university chemistry professors) and nonscience major introductory chemistry students, enrolled in a course at the university level, to solve paired algorithmic and conceptual problems. Of the 180 students involved, the problem-solving…
Using Grey Wolf Algorithm to Solve the Capacitated Vehicle Routing Problem
NASA Astrophysics Data System (ADS)
Korayem, L.; Khorsid, M.; Kassem, S. S.
2015-05-01
The capacitated vehicle routing problem (CVRP) is a class of the vehicle routing problems (VRPs). In CVRP a set of identical vehicles having fixed capacities are required to fulfill customers' demands for a single commodity. The main objective is to minimize the total cost or distance traveled by the vehicles while satisfying a number of constraints, such as: the capacity constraint of each vehicle, logical flow constraints, etc. One of the methods employed in solving the CVRP is the cluster-first route-second method. It is a technique based on grouping of customers into a number of clusters, where each cluster is served by one vehicle. Once clusters are formed, a route determining the best sequence to visit customers is established within each cluster. The recently bio-inspired grey wolf optimizer (GWO), introduced in 2014, has proven to be efficient in solving unconstrained, as well as, constrained optimization problems. In the current research, our main contributions are: combining GWO with the traditional K-means clustering algorithm to generate the ‘K-GWO’ algorithm, deriving a capacitated version of the K-GWO algorithm by incorporating a capacity constraint into the aforementioned algorithm, and finally, developing 2 new clustering heuristics. The resulting algorithm is used in the clustering phase of the cluster-first route-second method to solve the CVR problem. The algorithm is tested on a number of benchmark problems with encouraging results.
Simulated annealing algorithm for solving chambering student-case assignment problem
NASA Astrophysics Data System (ADS)
Ghazali, Saadiah; Abdul-Rahman, Syariza
2015-12-01
The problem related to project assignment problem is one of popular practical problem that appear nowadays. The challenge of solving the problem raise whenever the complexity related to preferences, the existence of real-world constraints and problem size increased. This study focuses on solving a chambering student-case assignment problem by using a simulated annealing algorithm where this problem is classified under project assignment problem. The project assignment problem is considered as hard combinatorial optimization problem and solving it using a metaheuristic approach is an advantage because it could return a good solution in a reasonable time. The problem of assigning chambering students to cases has never been addressed in the literature before. For the proposed problem, it is essential for law graduates to peruse in chambers before they are qualified to become legal counselor. Thus, assigning the chambering students to cases is a critically needed especially when involving many preferences. Hence, this study presents a preliminary study of the proposed project assignment problem. The objective of the study is to minimize the total completion time for all students in solving the given cases. This study employed a minimum cost greedy heuristic in order to construct a feasible initial solution. The search then is preceded with a simulated annealing algorithm for further improvement of solution quality. The analysis of the obtained result has shown that the proposed simulated annealing algorithm has greatly improved the solution constructed by the minimum cost greedy heuristic. Hence, this research has demonstrated the advantages of solving project assignment problem by using metaheuristic techniques.
Heuristic algorithms for solving of the tool routing problem for CNC cutting machines
NASA Astrophysics Data System (ADS)
Chentsov, P. A.; Petunin, A. A.; Sesekin, A. N.; Shipacheva, E. N.; Sholohov, A. E.
2015-11-01
The article is devoted to the problem of minimizing the path of the cutting tool to shape cutting machines began. This problem can be interpreted as a generalized traveling salesman problem. Earlier version of the dynamic programming method to solve this problem was developed. Unfortunately, this method allows to process an amount not exceeding thirty circuits. In this regard, the task of constructing quasi-optimal route becomes relevant. In this paper we propose options for quasi-optimal greedy algorithms. Comparison of the results of exact and approximate algorithms is given.
A parallel algorithm for solving the n-queens problem based on inspired computational model.
Wang, Zhaocai; Huang, Dongmei; Tan, Jian; Liu, Taigang; Zhao, Kai; Li, Lei
2015-05-01
DNA computing provides a promising method to solve the computationally intractable problems. The n-queens problem is a well-known NP-hard problem, which arranges n queens on an n × n board in different rows, columns and diagonals in order to avoid queens attack each other. In this paper, we present a novel parallel DNA algorithm for solving the n-queens problem using DNA molecular operations based on a biologically inspired computational model. For the n-queens problem, we reasonably design flexible length DNA strands representing elements of the allocation matrix, take appropriate biologic manipulations and get the solutions of the n-queens problem in proper length and O(n(2)) time complexity. We extend the application of DNA molecular operations, simultaneity simplify the complexity of the computation and simulate to verify the feasibility of the DNA algorithm. PMID:25817410
Liu, Haorui; Yi, Fengyan; Yang, Heli
2016-01-01
The shuffled frog leaping algorithm (SFLA) easily falls into local optimum when it solves multioptimum function optimization problem, which impacts the accuracy and convergence speed. Therefore this paper presents grouped SFLA for solving continuous optimization problems combined with the excellent characteristics of cloud model transformation between qualitative and quantitative research. The algorithm divides the definition domain into several groups and gives each group a set of frogs. Frogs of each region search in their memeplex, and in the search process the algorithm uses the “elite strategy” to update the location information of existing elite frogs through cloud model algorithm. This method narrows the searching space and it can effectively improve the situation of a local optimum; thus convergence speed and accuracy can be significantly improved. The results of computer simulation confirm this conclusion. PMID:26819584
The delayed coupling method: An algorithm for solving banded diagonal matrix problems in parallel
Mattor, N.; Williams, T.J.; Hewett, D.W.; Dimits, A.M.
1997-09-01
We present a new algorithm for solving banded diagonal matrix problems efficiently on distributed-memory parallel computers, designed originally for use in dynamic alternating-direction implicit partial differential equation solvers. The algorithm optimizes efficiency with respect to the number of numerical operations and to the amount of interprocessor communication. This is called the ``delayed coupling method`` because the communication is deferred until needed. We focus here on tridiagonal and periodic tridiagonal systems.
Tracking Problem Solving by Multivariate Pattern Analysis and Hidden Markov Model Algorithms
ERIC Educational Resources Information Center
Anderson, John R.
2012-01-01
Multivariate pattern analysis can be combined with Hidden Markov Model algorithms to track the second-by-second thinking as people solve complex problems. Two applications of this methodology are illustrated with a data set taken from children as they interacted with an intelligent tutoring system for algebra. The first "mind reading" application…
A cuckoo search algorithm by Lévy flights for solving reliability redundancy allocation problems
NASA Astrophysics Data System (ADS)
Valian, Ehsan; Valian, Elham
2013-11-01
A new metaheuristic optimization algorithm, called cuckoo search (CS), was recently developed by Yang and Deb (2009, 2010). This article uses CS and Lévy flights to solve the reliability redundancy allocation problem. The redundancy allocation problem involves setting reliability objectives for components or subsystems in order to meet the resource consumption constraint, e.g. the total cost. The difficulties facing the redundancy allocation problem are to maintain feasibility with respect to three nonlinear constraints, namely, cost, weight and volume-related constraints. The redundancy allocation problems have been studied in the literature for decades, usually using mathematical programming or metaheuristic optimization algorithms. The performance of the algorithm is tested on five well-known reliability redundancy allocation problems and is compared with several well-known methods. Simulation results demonstrate that the optimal solutions obtained by CS are better than the best solutions obtained by other methods.
Solving constrained minimum-time robot problems using the sequential gradient restoration algorithm
NASA Technical Reports Server (NTRS)
Lee, Allan Y.
1991-01-01
Three constrained minimum-time control problems of a two-link manipulator are solved using the Sequential Gradient and Restoration Algorithm (SGRA). The inequality constraints considered are reduced via Valentine-type transformations to nondifferential path equality constraints. The SGRA is then used to solve these transformed problems with equality constraints. The results obtained indicate that at least one of the two controls is at its limits at any instant in time. The remaining control then adjusts itself so that none of the system constraints is violated. Hence, the minimum-time control is either a pure bang-bang control or a combined bang-bang/singular control.
The minimal residual QR-factorization algorithm for reliably solving subset regression problems
NASA Technical Reports Server (NTRS)
Verhaegen, M. H.
1987-01-01
A new algorithm to solve test subset regression problems is described, called the minimal residual QR factorization algorithm (MRQR). This scheme performs a QR factorization with a new column pivoting strategy. Basically, this strategy is based on the change in the residual of the least squares problem. Furthermore, it is demonstrated that this basic scheme might be extended in a numerically efficient way to combine the advantages of existing numerical procedures, such as the singular value decomposition, with those of more classical statistical procedures, such as stepwise regression. This extension is presented as an advisory expert system that guides the user in solving the subset regression problem. The advantages of the new procedure are highlighted by a numerical example.
Solving the SAT problem using a DNA computing algorithm based on ligase chain reaction.
Wang, Xiaolong; Bao, Zhenmin; Hu, Jingjie; Wang, Shi; Zhan, Aibin
2008-01-01
A new DNA computing algorithm based on a ligase chain reaction is demonstrated to solve an SAT problem. The proposed DNA algorithm can solve an n-variable m-clause SAT problem in m steps and the computation time required is O (3m+n). Instead of generating the full-solution DNA library, we start with an empty test tube and then generate solutions that partially satisfy the SAT formula. These partial solutions are then extended step by step by the ligation of new variables using Taq DNA ligase. Correct strands are amplified and false strands are pruned by a ligase chain reaction (LCR) as soon as they fail to satisfy the conditions. If we score and sort the clauses, we can use this algorithm to markedly reduce the number of DNA strands required throughout the computing process. In a computer simulation, the maximum number of DNA strands required was 2(0.48n) when n=50, and the exponent ratio varied inversely with the number of variables n and the clause/variable ratio m/n. This algorithm is highly space-efficient and error-tolerant compared to conventional brute-force searching, and thus can be scaled-up to solve large and hard SAT problems. PMID:17904730
Liu, Derong; Li, Hongliang; Wang, Ding
2015-06-01
In this paper, we establish error bounds of adaptive dynamic programming algorithms for solving undiscounted infinite-horizon optimal control problems of discrete-time deterministic nonlinear systems. We consider approximation errors in the update equations of both value function and control policy. We utilize a new assumption instead of the contraction assumption in discounted optimal control problems. We establish the error bounds for approximate value iteration based on a new error condition. Furthermore, we also establish the error bounds for approximate policy iteration and approximate optimistic policy iteration algorithms. It is shown that the iterative approximate value function can converge to a finite neighborhood of the optimal value function under some conditions. To implement the developed algorithms, critic and action neural networks are used to approximate the value function and control policy, respectively. Finally, a simulation example is given to demonstrate the effectiveness of the developed algorithms. PMID:25751878
NASA Astrophysics Data System (ADS)
Jiang, Mingfeng; Xia, Ling; Shou, Guofa; Tang, Min
2007-03-01
Computing epicardial potentials from body surface potentials constitutes one form of ill-posed inverse problem of electrocardiography (ECG). To solve this ECG inverse problem, the Tikhonov regularization and truncated singular-value decomposition (TSVD) methods have been commonly used to overcome the ill-posed property by imposing constraints on the magnitudes or derivatives of the computed epicardial potentials. Such direct regularization methods, however, are impractical when the transfer matrix is large. The least-squares QR (LSQR) method, one of the iterative regularization methods based on Lanczos bidiagonalization and QR factorization, has been shown to be numerically more reliable in various circumstances than the other methods considered. This LSQR method, however, to our knowledge, has not been introduced and investigated for the ECG inverse problem. In this paper, the regularization properties of the Krylov subspace iterative method of LSQR for solving the ECG inverse problem were investigated. Due to the 'semi-convergence' property of the LSQR method, the L-curve method was used to determine the stopping iteration number. The performance of the LSQR method for solving the ECG inverse problem was also evaluated based on a realistic heart-torso model simulation protocol. The results show that the inverse solutions recovered by the LSQR method were more accurate than those recovered by the Tikhonov and TSVD methods. In addition, by combing the LSQR with genetic algorithms (GA), the performance can be improved further. It suggests that their combination may provide a good scheme for solving the ECG inverse problem.
A firefly algorithm for solving competitive location-design problem: a case study
NASA Astrophysics Data System (ADS)
Sadjadi, Seyed Jafar; Ashtiani, Milad Gorji; Ramezanian, Reza; Makui, Ahmad
2016-07-01
This paper aims at determining the optimal number of new facilities besides specifying both the optimal location and design level of them under the budget constraint in a competitive environment by a novel hybrid continuous and discrete firefly algorithm. A real-world application of locating new chain stores in the city of Tehran, Iran, is used and the results are analyzed. In addition, several examples have been solved to evaluate the efficiency of the proposed model and algorithm. The results demonstrate that the performed method provides good-quality results for the test problems.
Wang, Zhaocai; Huang, Dongmei; Meng, Huajun; Tang, Chengpei
2013-10-01
The minimum spanning tree (MST) problem is to find minimum edge connected subsets containing all the vertex of a given undirected graph. It is a vitally important NP-complete problem in graph theory and applied mathematics, having numerous real life applications. Moreover in previous studies, DNA molecular operations usually were used to solve NP-complete head-to-tail path search problems, rarely for NP-hard problems with multi-lateral path solutions result, such as the minimum spanning tree problem. In this paper, we present a new fast DNA algorithm for solving the MST problem using DNA molecular operations. For an undirected graph with n vertex and m edges, we reasonably design flexible length DNA strands representing the vertex and edges, take appropriate steps and get the solutions of the MST problem in proper length range and O(3m+n) time complexity. We extend the application of DNA molecular operations and simultaneity simplify the complexity of the computation. Results of computer simulative experiments show that the proposed method updates some of the best known values with very short time and that the proposed method provides a better performance with solution accuracy over existing algorithms. PMID:23871964
Problem Solving in the Professions.
ERIC Educational Resources Information Center
Jackling, Noel; And Others
1990-01-01
It is proposed that algorithms and heuristics are useful in improving professional problem-solving abilities when contextualized within the academic discipline. A basic algorithm applied to problem solving in undergraduate engineering education and a similar algorithm applicable to legal problems are used as examples. Problem complexity and…
Solving large-scale real-world telecommunication problems using a grid-based genetic algorithm
NASA Astrophysics Data System (ADS)
Luna, Francisco; Nebro, Antonio; Alba, Enrique; Durillo, Juan
2008-11-01
This article analyses the use of a grid-based genetic algorithm (GrEA) to solve a real-world instance of a problem from the telecommunication domain. The problem, known as automatic frequency planning (AFP), is used in a global system for mobile communications (GSM) networks to assign a number of fixed frequencies to a set of GSM transceivers located in the antennae of a cellular phone network. Real data instances of the AFP are very difficult to solve owing to the NP-hard nature of the problem, so combining grid computing and metaheuristics turns out to be a way to provide satisfactory solutions in a reasonable amount of time. GrEA has been deployed on a grid with up to 300 processors to solve an AFP instance of 2612 transceivers. The results not only show that significant running time reductions are achieved, but that the search capability of GrEA clearly outperforms that of the equivalent non-grid algorithm.
Solving multi-objective job shop scheduling problems using a non-dominated sorting genetic algorithm
NASA Astrophysics Data System (ADS)
Piroozfard, Hamed; Wong, Kuan Yew
2015-05-01
The efforts of finding optimal schedules for the job shop scheduling problems are highly important for many real-world industrial applications. In this paper, a multi-objective based job shop scheduling problem by simultaneously minimizing makespan and tardiness is taken into account. The problem is considered to be more complex due to the multiple business criteria that must be satisfied. To solve the problem more efficiently and to obtain a set of non-dominated solutions, a meta-heuristic based non-dominated sorting genetic algorithm is presented. In addition, task based representation is used for solution encoding, and tournament selection that is based on rank and crowding distance is applied for offspring selection. Swapping and insertion mutations are employed to increase diversity of population and to perform intensive search. To evaluate the modified non-dominated sorting genetic algorithm, a set of modified benchmarking job shop problems obtained from the OR-Library is used, and the results are considered based on the number of non-dominated solutions and quality of schedules obtained by the algorithm.
Wang, Zhaocai; Pu, Jun; Cao, Liling; Tan, Jian
2015-01-01
The unbalanced assignment problem (UAP) is to optimally resolve the problem of assigning n jobs to m individuals (m < n), such that minimum cost or maximum profit obtained. It is a vitally important Non-deterministic Polynomial (NP) complete problem in operation management and applied mathematics, having numerous real life applications. In this paper, we present a new parallel DNA algorithm for solving the unbalanced assignment problem using DNA molecular operations. We reasonably design flexible-length DNA strands representing different jobs and individuals, take appropriate steps, and get the solutions of the UAP in the proper length range and O(mn) time. We extend the application of DNA molecular operations and simultaneity to simplify the complexity of the computation. PMID:26512650
Wang, Zhaocai; Pu, Jun; Cao, Liling; Tan, Jian
2015-01-01
The unbalanced assignment problem (UAP) is to optimally resolve the problem of assigning n jobs to m individuals (m < n), such that minimum cost or maximum profit obtained. It is a vitally important Non-deterministic Polynomial (NP) complete problem in operation management and applied mathematics, having numerous real life applications. In this paper, we present a new parallel DNA algorithm for solving the unbalanced assignment problem using DNA molecular operations. We reasonably design flexible-length DNA strands representing different jobs and individuals, take appropriate steps, and get the solutions of the UAP in the proper length range and O(mn) time. We extend the application of DNA molecular operations and simultaneity to simplify the complexity of the computation. PMID:26512650
Solving the container pre-marshalling problem using variable length genetic algorithms
NASA Astrophysics Data System (ADS)
Gheith, Mohamed; Eltawil, Amr B.; Harraz, Nermine A.
2016-04-01
In container terminals, the yard area consists of a set of blocks, which consists of a set of bays. Each bay consists of a set of stacks, which consists of a set of tiers. In the container pre-marshalling problem, an initial layout of a bay is converted to a final desired layout. The final layout follows the given loading schedule of this bay. This has a direct impact on the most important container terminal performance measure: the vessel loading time. The deviation between the current layout and the desired layout is expressed by the value of the mis-overlays. The objective of the pre-marshalling problem is to eliminate the mis-overlays with the minimum number of container movements. In this article, a variable chromosome length genetic algorithm was applied to solve the problem. The results of the new solution approach were compared against benchmark instances and the results were remarkably better.
A hybrid algorithm for solving the EEG inverse problem from spatio-temporal EEG data.
Crevecoeur, Guillaume; Hallez, Hans; Van Hese, Peter; D'Asseler, Yves; Dupré, Luc; Van de Walle, Rik
2008-08-01
Epilepsy is a neurological disorder caused by intense electrical activity in the brain. The electrical activity, which can be modelled through the superposition of several electrical dipoles, can be determined in a non-invasive way by analysing the electro-encephalogram. This source localization requires the solution of an inverse problem. Locally convergent optimization algorithms may be trapped in local solutions and when using global optimization techniques, the computational effort can become expensive. Fast recovery of the electrical sources becomes difficult that way. Therefore, there is a need to solve the inverse problem in an accurate and fast way. This paper performs the localization of multiple dipoles using a global-local hybrid algorithm. Global convergence is guaranteed by using space mapping techniques and independent component analysis in a computationally efficient way. The accuracy is locally obtained by using the Recursively Applied and Projected-MUltiple Signal Classification (RAP-MUSIC) algorithm. When using this hybrid algorithm, a four times faster solution is obtained. PMID:18427852
NASA Astrophysics Data System (ADS)
Piotrowski, J.
2010-07-01
This paper presents two extensions of Kalker's algorithm Fastsim of the simplified theory of rolling contact. The first extension is for solving tangential contact problems with the coefficient of friction depending on slip velocity. Two friction laws have been considered: with and without recuperation of the static friction. According to the tribological hypothesis for metallic bodies shear failure, the friction law without recuperation of static friction is more suitable for wheel and rail than the other one. Sample results present local quantities inside the contact area (division to slip and adhesion, traction) as well as global ones (creep forces as functions of creepages and rolling velocity). For the coefficient of friction diminishing with slip, the creep forces decay after reaching the maximum and they depend on the rolling velocity. The second extension is for solving tangential contact problems with friction anisotropy characterised by a convex set of the permissible tangential tractions. The effect of the anisotropy has been shown on examples of rolling without spin and in the presence of pure spin for the elliptical set. The friction anisotropy influences tangential tractions and creep forces. Sample results present local and global quantities. Both extensions have been described with the same language of formulation and they may be merged into one, joint algorithm.
NASA Astrophysics Data System (ADS)
Al-Ma'shumah, Fathimah; Permana, Dony; Sidarto, Kuntjoro Adji
2015-12-01
Customer Lifetime Value is an important and useful concept in marketing. One of its benefits is to help a company for budgeting marketing expenditure for customer acquisition and customer retention. Many mathematical models have been introduced to calculate CLV considering the customer retention/migration classification scheme. A fairly new class of these models which will be described in this paper uses Markov Chain Models (MCM). This class of models has the major advantage for its flexibility to be modified to several different cases/classification schemes. In this model, the probabilities of customer retention and acquisition play an important role. From Pfeifer and Carraway, 2000, the final formula of CLV obtained from MCM usually contains nonlinear form of the transition probability matrix. This nonlinearity makes the inverse problem of CLV difficult to solve. This paper aims to solve this inverse problem, yielding the approximate transition probabilities for the customers, by applying metaheuristic optimization algorithm developed by Yang, 2013, Flower Pollination Algorithm. The major interpretation of obtaining the transition probabilities are to set goals for marketing teams in keeping the relative frequencies of customer acquisition and customer retention.
Automatic Combination of Operators in a Genetic Algorithm to Solve the Traveling Salesman Problem
2015-01-01
Genetic algorithms are powerful search methods inspired by Darwinian evolution. To date, they have been applied to the solution of many optimization problems because of the easy use of their properties and their robustness in finding good solutions to difficult problems. The good operation of genetic algorithms is due in part to its two main variation operators, namely, crossover and mutation operators. Typically, in the literature, we find the use of a single crossover and mutation operator. However, there are studies that have shown that using multi-operators produces synergy and that the operators are mutually complementary. Using multi-operators is not a simple task because which operators to use and how to combine them must be determined, which in itself is an optimization problem. In this paper, it is proposed that the task of exploring the different combinations of the crossover and mutation operators can be carried out by evolutionary computing. The crossover and mutation operators used are those typically used for solving the traveling salesman problem. The process of searching for good combinations was effective, yielding appropriate and synergic combinations of the crossover and mutation operators. The numerical results show that the use of the combination of operators obtained by evolutionary computing is better than the use of a single operator and the use of multi-operators combined in the standard way. The results were also better than those of the last operators reported in the literature. PMID:26367182
He, Qiang; Hu, Xiangtao; Ren, Hong; Zhang, Hongqi
2015-11-01
A novel artificial fish swarm algorithm (NAFSA) is proposed for solving large-scale reliability-redundancy allocation problem (RAP). In NAFSA, the social behaviors of fish swarm are classified in three ways: foraging behavior, reproductive behavior, and random behavior. The foraging behavior designs two position-updating strategies. And, the selection and crossover operators are applied to define the reproductive ability of an artificial fish. For the random behavior, which is essentially a mutation strategy, the basic cloud generator is used as the mutation operator. Finally, numerical results of four benchmark problems and a large-scale RAP are reported and compared. NAFSA shows good performance in terms of computational accuracy and computational efficiency for large scale RAP. PMID:26474934
NASA Astrophysics Data System (ADS)
Zamirian, M.; Kamyad, A. V.; Farahi, M. H.
2009-09-01
In this Letter a new approach for solving optimal path planning problems for a single rigid and free moving object in a two and three dimensional space in the presence of stationary or moving obstacles is presented. In this approach the path planning problems have some incompatible objectives such as the length of path that must be minimized, the distance between the path and obstacles that must be maximized and etc., then a multi-objective dynamic optimization problem (MODOP) is achieved. Considering the imprecise nature of decision maker's (DM) judgment, these multiple objectives are viewed as fuzzy variables. By determining intervals for the values of these fuzzy variables, flexible monotonic decreasing or increasing membership functions are determined as the degrees of satisfaction of these fuzzy variables on their intervals. Then, the optimal path planning policy is searched by maximizing the aggregated fuzzy decision values, resulting in a fuzzy multi-objective dynamic optimization problem (FMODOP). Using a suitable t-norm, the FMODOP is converted into a non-linear dynamic optimization problem (NLDOP). By using parametrization method and some calculations, the NLDOP is converted into the sequence of conventional non-linear programming problems (NLPP). It is proved that the solution of this sequence of the NLPPs tends to a Pareto optimal solution which, among other Pareto optimal solutions, has the best satisfaction of DM for the MODOP. Finally, the above procedure as a novel algorithm integrating parametrization method and fuzzy aggregation to solve the MODOP is proposed. Efficiency of our approach is confirmed by some numerical examples.
Martín H, José Antonio
2013-01-01
Many practical problems in almost all scientific and technological disciplines have been classified as computationally hard (NP-hard or even NP-complete). In life sciences, combinatorial optimization problems frequently arise in molecular biology, e.g., genome sequencing; global alignment of multiple genomes; identifying siblings or discovery of dysregulated pathways. In almost all of these problems, there is the need for proving a hypothesis about certain property of an object that can be present if and only if it adopts some particular admissible structure (an NP-certificate) or be absent (no admissible structure), however, none of the standard approaches can discard the hypothesis when no solution can be found, since none can provide a proof that there is no admissible structure. This article presents an algorithm that introduces a novel type of solution method to "efficiently" solve the graph 3-coloring problem; an NP-complete problem. The proposed method provides certificates (proofs) in both cases: present or absent, so it is possible to accept or reject the hypothesis on the basis of a rigorous proof. It provides exact solutions and is polynomial-time (i.e., efficient) however parametric. The only requirement is sufficient computational power, which is controlled by the parameter α∈N. Nevertheless, here it is proved that the probability of requiring a value of α>k to obtain a solution for a random graph decreases exponentially: P(α>k)≤2(-(k+1)), making tractable almost all problem instances. Thorough experimental analyses were performed. The algorithm was tested on random graphs, planar graphs and 4-regular planar graphs. The obtained experimental results are in accordance with the theoretical expected results. PMID:23349711
Meta-heuristic algorithm to solve two-sided assembly line balancing problems
NASA Astrophysics Data System (ADS)
Wirawan, A. D.; Maruf, A.
2016-02-01
Two-sided assembly line is a set of sequential workstations where task operations can be performed at two sides of the line. This type of line is commonly used for the assembly of large-sized products: cars, buses, and trucks. This paper propose a Decoding Algorithm with Teaching-Learning Based Optimization (TLBO), a recently developed nature-inspired search method to solve the two-sided assembly line balancing problem (TALBP). The algorithm aims to minimize the number of mated-workstations for the given cycle time without violating the synchronization constraints. The correlation between the input parameters and the emergence point of objective function value is tested using scenarios generated by design of experiments. A two-sided assembly line operated in an Indonesia's multinational manufacturing company is considered as the object of this paper. The result of the proposed algorithm shows reduction of workstations and indicates that there is negative correlation between the emergence point of objective function value and the size of population used.
NASA Astrophysics Data System (ADS)
Gurarslan, Gurhan; Karahan, Halil
2015-09-01
In this study, an accurate model was developed for solving problems of groundwater-pollution-source identification. In the developed model, the numerical simulations of flow and pollutant transport in groundwater were carried out using MODFLOW and MT3DMS software. The optimization processes were carried out using a differential evolution algorithm. The performance of the developed model was tested on two hypothetical aquifer models using real and noisy observation data. In the first model, the release histories of the pollution sources were determined assuming that the numbers, locations and active stress periods of the sources are known. In the second model, the release histories of the pollution sources were determined assuming that there is no information on the sources. The results obtained by the developed model were found to be better than those reported in literature.
NASA Astrophysics Data System (ADS)
Xu, Ye; Wang, Ling; Wang, Shengyao; Liu, Min
2014-09-01
In this article, an effective hybrid immune algorithm (HIA) is presented to solve the distributed permutation flow-shop scheduling problem (DPFSP). First, a decoding method is proposed to transfer a job permutation sequence to a feasible schedule considering both factory dispatching and job sequencing. Secondly, a local search with four search operators is presented based on the characteristics of the problem. Thirdly, a special crossover operator is designed for the DPFSP, and mutation and vaccination operators are also applied within the framework of the HIA to perform an immune search. The influence of parameter setting on the HIA is investigated based on the Taguchi method of design of experiment. Extensive numerical testing results based on 420 small-sized instances and 720 large-sized instances are provided. The effectiveness of the HIA is demonstrated by comparison with some existing heuristic algorithms and the variable neighbourhood descent methods. New best known solutions are obtained by the HIA for 17 out of 420 small-sized instances and 585 out of 720 large-sized instances.
Solving University Course Timetabling Problems by a Novel Genetic Algorithm Based on Flow
NASA Astrophysics Data System (ADS)
Yue, Zhenhua; Li, Shanqiang; Xiao, Long
Since the University Course Timetabling Problem (UCTP) is a typical sort of combinatorial issues, many conventional methods turn out to be unavailable when confronted with this complex problem where lots of constraints need to be satisfied especially with the class-flow between floors added. Considering the supreme density of students between classes, this paper proposes a novel algorithm integrating Simulated Annealing (SA) into the Genetic Algorithm (GA) for solving the UCTP with respect to the class-flow where SA is incorporated into the competition and selection strategy of GA and concerning the class-flow caused by the assigned timetable, a modified fitness function is presented that determines the survival of generations. Moreover, via the exchange of lecturing classrooms the timetable with minimum class-flow is eventually derived with the values of defined fitness function. Finally, in terms of the definitions above, a simulation of virtual situation is implemented and the experimental results indicate that the proposed model of classroom arrangement in the paper maintains a high efficiency.
ERIC Educational Resources Information Center
Kiesmuller, Ulrich
2009-01-01
At schools special learning and programming environments are often used in the field of algorithms. Particularly with regard to computer science lessons in secondary education, they are supposed to help novices to learn the basics of programming. In several parts of Germany (e.g., Bavaria) these fundamentals are taught as early as in the seventh…
A configuration space Monte Carlo algorithm for solving the nuclear pairing problem
NASA Astrophysics Data System (ADS)
Lingle, Mark
Nuclear pairing correlations using Quantum Monte Carlo are studied in this dissertation. We start by defining the nuclear pairing problem and discussing several historical methods developed to solve this problem, paying special attention to the applicability of such methods. A numerical example discussing pairing correlations in several calcium isotopes using the BCS and Exact Pairing solutions are presented. The ground state energies, correlation energies, and occupation numbers are compared to determine the applicability of each approach to realistic cases. Next we discuss some generalities related to the theory of Markov Chains and Quantum Monte Carlo in regards to nuclear structure. Finally we present our configuration space Monte Carlo algorithm starting from a discussion of a path integral approach by the authors. Some general features of the Pairing Hamiltonian that boost the effectiveness of a configuration space Monte Carlo approach are mentioned. The full details of our method are presented and special attention is paid to convergence and error control. We present a series of examples illustrating the effectiveness of our approach. These include situations with non-constant pairing strengths, limits when pairing correlations are weak, the computation of excited states, and problems when the relevant configuration space is large. We conclude with a chapter examining some of the effects of continuum states in 24O.
NASA Astrophysics Data System (ADS)
Bao, Xingxian; Cao, Aixia; Zhang, Jing
2016-07-01
Modal parameters estimation plays an important role for structural health monitoring. Accurately estimating the modal parameters of structures is more challenging as the measured vibration response signals are contaminated with noise. This study develops a mathematical algorithm of solving the partially described inverse singular value problem (PDISVP) combined with the complex exponential (CE) method to estimate the modal parameters. The PDISVP solving method is to reconstruct an L2-norm optimized (filtered) data matrix from the measured (noisy) data matrix, when the prescribed data constraints are one or several sets of singular triplets of the matrix. The measured data matrix is Hankel structured, which is constructed based on the measured impulse response function (IRF). The reconstructed matrix must maintain the Hankel structure, and be lowered in rank as well. Once the filtered IRF is obtained, the CE method can be applied to extract the modal parameters. Two physical experiments, including a steel cantilever beam with 10 accelerometers mounted, and a steel plate with 30 accelerometers mounted, excited by an impulsive load, respectively, are investigated to test the applicability of the proposed scheme. In addition, the consistency diagram is proposed to exam the agreement among the modal parameters estimated from those different accelerometers. Results indicate that the PDISVP-CE method can significantly remove noise from measured signals and accurately estimate the modal frequencies and damping ratios.
ERIC Educational Resources Information Center
Salta, Katerina; Tzougraki, Chryssa
2011-01-01
The students' performance in various types of problems dealing with the conservation of matter during chemical reactions has been investigated at different levels of schooling. The participants were 499 ninth grade (ages 14, 15 years) and 624 eleventh grade (ages 16, 17 years) Greek students. Data was collected using a written questionnaire…
NASA Astrophysics Data System (ADS)
Wang, J.; Cai, X.
2007-12-01
A water resources system can be defined as a large-scale spatial system, within which distributed ecological system interacts with the stream network and ground water system. Water resources management, the causative factors and hence the solutions to be developed have a significant spatial dimension. This motivates a modeling analysis of water resources management within a spatial analytical framework, where data is usually geo- referenced and in the form of a map. One of the important functions of Geographic information systems (GIS) is to identify spatial patterns of environmental variables. The role of spatial patterns in water resources management has been well established in the literature particularly regarding how to design better spatial patterns for satisfying the designated objectives of water resources management. Evolutionary algorithms (EA) have been demonstrated to be successful in solving complex optimization models for water resources management due to its flexibility to incorporate complex simulation models in the optimal search procedure. The idea of combining GIS and EA motivates the development and application of spatial evolutionary algorithms (SEA). SEA assimilates spatial information into EA, and even changes the representation and operators of EA. In an EA used for water resources management, the mathematical optimization model should be modified to account the spatial patterns; however, spatial patterns are usually implicit, and it is difficult to impose appropriate patterns to spatial data. Also it is difficult to express complex spatial patterns by explicit constraints included in the EA. The GIS can help identify the spatial linkages and correlations based on the spatial knowledge of the problem. These linkages are incorporated in the fitness function for the preference of the compatible vegetation distribution. Unlike a regular GA for spatial models, the SEA employs a special hierarchical hyper-population and spatial genetic operators
Solving mixed integer nonlinear programming problems using spiral dynamics optimization algorithm
NASA Astrophysics Data System (ADS)
Kania, Adhe; Sidarto, Kuntjoro Adji
2016-02-01
Many engineering and practical problem can be modeled by mixed integer nonlinear programming. This paper proposes to solve the problem with modified spiral dynamics inspired optimization method of Tamura and Yasuda. Four test cases have been examined, including problem in engineering and sport. This method succeeds in obtaining the optimal result in all test cases.
A hybrid symbolic/finite-element algorithm for solving nonlinear optimal control problems
NASA Technical Reports Server (NTRS)
Bless, Robert R.; Hodges, Dewey H.
1991-01-01
The general code described is capable of solving difficult nonlinear optimal control problems by using finite elements and a symbolic manipulator. Quick and accurate solutions are obtained with a minimum for user interaction. Since no user programming is required for most problems, there are tremendous savings to be gained in terms of time and money.
NASA Astrophysics Data System (ADS)
Hetmaniok, Edyta
2015-08-01
In this paper the procedure for solving the inverse problem for the binary alloy solidification in the casting mould is presented. Proposed approach is based on the mathematical model suitable for describing the investigated solidification process, the lever arm model describing the macrosegregation process, the finite element method for solving the direct problem and the artificial bee colony algorithm for minimizing the functional expressing the error of approximate solution. Goal of the discussed inverse problem is the reconstruction of heat transfer coefficient and distribution of temperature in investigated region on the basis of known measurements of temperature.
NASA Astrophysics Data System (ADS)
Hetmaniok, Edyta
2016-07-01
In this paper the procedure for solving the inverse problem for the binary alloy solidification in the casting mould is presented. Proposed approach is based on the mathematical model suitable for describing the investigated solidification process, the lever arm model describing the macrosegregation process, the finite element method for solving the direct problem and the artificial bee colony algorithm for minimizing the functional expressing the error of approximate solution. Goal of the discussed inverse problem is the reconstruction of heat transfer coefficient and distribution of temperature in investigated region on the basis of known measurements of temperature.
Application of a Chimera Full Potential Algorithm for Solving Aerodynamic Problems
NASA Technical Reports Server (NTRS)
Holst, Terry L.; Kwak, Dochan (Technical Monitor)
1997-01-01
A numerical scheme utilizing a chimera zonal grid approach for solving the three dimensional full potential equation is described. Special emphasis is placed on describing the spatial differencing algorithm around the chimera interface. Results from two spatial discretization variations are presented; one using a hybrid first-order/second-order-accurate scheme and the second using a fully second-order-accurate scheme. The presentation is highlighted with a number of transonic wing flow field computations.
NASA Astrophysics Data System (ADS)
Schütze, Niels; Wöhling, Thomas; de Play, Michael
2010-05-01
Some real-world optimization problems in water resources have a high-dimensional space of decision variables and more than one objective function. In this work, we compare three general-purpose, multi-objective simulation optimization algorithms, namely NSGA-II, AMALGAM, and CMA-ES-MO when solving three real case Multi-objective Optimization Problems (MOPs): (i) a high-dimensional soil hydraulic parameter estimation problem; (ii) a multipurpose multi-reservoir operation problem; and (iii) a scheduling problem in deficit irrigation. We analyze the behaviour of the three algorithms on these test problems considering their formulations ranging from 40 up to 120 decision variables and 2 to 4 objectives. The computational effort required by each algorithm in order to reach the true Pareto front is also analyzed.
A Prefiltered Cuckoo Search Algorithm with Geometric Operators for Solving Sudoku Problems
Crawford, Broderick; Galleguillos, Cristian; Paredes, Fernando
2014-01-01
The Sudoku is a famous logic-placement game, originally popularized in Japan and today widely employed as pastime and as testbed for search algorithms. The classic Sudoku consists in filling a 9 × 9 grid, divided into nine 3 × 3 regions, so that each column, row, and region contains different digits from 1 to 9. This game is known to be NP-complete, with existing various complete and incomplete search algorithms able to solve different instances of it. In this paper, we present a new cuckoo search algorithm for solving Sudoku puzzles combining prefiltering phases and geometric operations. The geometric operators allow one to correctly move toward promising regions of the combinatorial space, while the prefiltering phases are able to previously delete from domains the values that do not conduct to any feasible solution. This integration leads to a more efficient domain filtering and as a consequence to a faster solving process. We illustrate encouraging experimental results where our approach noticeably competes with the best approximate methods reported in the literature. PMID:24707205
A prefiltered cuckoo search algorithm with geometric operators for solving Sudoku problems.
Soto, Ricardo; Crawford, Broderick; Galleguillos, Cristian; Monfroy, Eric; Paredes, Fernando
2014-01-01
The Sudoku is a famous logic-placement game, originally popularized in Japan and today widely employed as pastime and as testbed for search algorithms. The classic Sudoku consists in filling a 9 × 9 grid, divided into nine 3 × 3 regions, so that each column, row, and region contains different digits from 1 to 9. This game is known to be NP-complete, with existing various complete and incomplete search algorithms able to solve different instances of it. In this paper, we present a new cuckoo search algorithm for solving Sudoku puzzles combining prefiltering phases and geometric operations. The geometric operators allow one to correctly move toward promising regions of the combinatorial space, while the prefiltering phases are able to previously delete from domains the values that do not conduct to any feasible solution. This integration leads to a more efficient domain filtering and as a consequence to a faster solving process. We illustrate encouraging experimental results where our approach noticeably competes with the best approximate methods reported in the literature. PMID:24707205
Genetic algorithms - A new technique for solving the neutron spectrum unfolding problem
NASA Astrophysics Data System (ADS)
Freeman, David W.; Ray Edwards, D.; Bolon, Albert E.
1999-04-01
A new technique utilizing genetic algorithms has been applied to the Bonner sphere neutron spectrum unfolding problem. Genetic algorithms are part of a relatively new field of "evolutionary" solution techniques that mimic living systems with computer-simulated "chromosome" solutions. Solutions mate and mutate to create better solutions. Several benchmark problems, considered representative of radiation protection environments, have been evaluated using the newly developed UMRGA code which implements the genetic algorithm unfolding technique. The results are compared with results from other well-established unfolding codes. The genetic algorithm technique works remarkably well and produces solutions with relatively high spectral qualities. UMRGA appears to be a superior technique in the absence of a priori data - it does not rely on "lucky" guesses of input spectra. Calculated personnel doses associated with the unfolded spectra match benchmark values within a few percent.
ERIC Educational Resources Information Center
DEVANE, J.R.; RIMOLDI, H.J.A.
CHANGES WERE STUDIED IN THE PROBLEM-SOLVING BEHAVIOR OF HIGH SCHOOL STUDENTS AS A FUNCTION OF A CAREFULLY DESIGNED TRAINING PROGRAM. TRAINING WAS DEFINED AS THE DEVELOPMENT OF STUDENT AWARENESS OF PROBLEM-SOLVING STRATEGIES USED. INSTRUMENTS WERE DEVELOPED AND REFINED TO MEASURE PROBLEM-SOLVING BEHAVIOR. SPECIFICALLY TESTED WAS THE FOLLOWING…
Mental Capacity and Working Memory in Chemistry: Algorithmic "versus" Open-Ended Problem Solving
ERIC Educational Resources Information Center
St Clair-Thompson, Helen; Overton, Tina; Bugler, Myfanwy
2012-01-01
Previous research has revealed that problem solving and attainment in chemistry are constrained by mental capacity and working memory. However, the terms mental capacity and working memory come from different theories of cognitive resources, and are assessed using different tasks. The current study examined the relationships between mental…
NASA Astrophysics Data System (ADS)
Shakir, Ali; AL-Khateeb, Belal; Shaker, Khalid; Jalab, Hamid A.
2014-12-01
The design of course timetables for academic institutions is a very difficult job due to the huge number of possible feasible timetables with respect to the problem size. This process contains lots of constraints that must be taken into account and a large search space to be explored, even if the size of the problem input is not significantly large. Different heuristic approaches have been proposed in the literature in order to solve this kind of problem. One of the efficient solution methods for this problem is tabu search. Different neighborhood structures based on different types of move have been defined in studies using tabu search. In this paper, different neighborhood structures on the operation of tabu search are examined. The performance of different neighborhood structures is tested over eleven benchmark datasets. The obtained results of every neighborhood structures are compared with each other. Results obtained showed the disparity between each neighborhood structures and another in terms of penalty cost.
Techniques of Problem Solving.
ERIC Educational Resources Information Center
Krantz, Steven G.
The purpose of this book is to teach the basic principles of problem solving in both mathematical and non-mathematical problems. The major components of the book consist of learning to translate verbal discussion into analytical data, learning problem solving methods for attacking collections of analytical questions or data, and building a…
Jiang, Mingfeng; Xia, Ling; Huang, Wenqing; Shou, Guofa; Liu, Feng; Crozier, Stuart
2009-10-01
Regularization is an effective method for the solution of ill-posed ECG inverse problems, such as computing epicardial potentials from body surface potentials. The aim of this work was to explore more robust regularization-based solutions through the application of subspace preconditioned LSQR (SP-LSQR) to the study of model-based ECG inverse problems. Here, we presented three different subspace splitting methods, i.e., SVD, wavelet transform and cosine transform schemes, to the design of the preconditioners for ill-posed problems, and to evaluate the performance of algorithms using a realistic heart-torso model simulation protocol. The results demonstrated that when compared with the LSQR, LSQR-Tik and Tik-LSQR method, the SP-LSQR produced higher efficiency and reconstructed more accurate epcicardial potential distributions. Amongst the three applied subspace splitting schemes, the SVD-based preconditioner yielded the best convergence rate and outperformed the other two in seeking the inverse solutions. Moreover, when optimized by the genetic algorithms (GA), the performances of SP-LSQR method were enhanced. The results from this investigation suggested that the SP-LSQR was a useful regularization technique for cardiac inverse problems. PMID:19564127
Parallel Algorithm Solves Coupled Differential Equations
NASA Technical Reports Server (NTRS)
Hayashi, A.
1987-01-01
Numerical methods adapted to concurrent processing. Algorithm solves set of coupled partial differential equations by numerical integration. Adapted to run on hypercube computer, algorithm separates problem into smaller problems solved concurrently. Increase in computing speed with concurrent processing over that achievable with conventional sequential processing appreciable, especially for large problems.
García-Arnau, Marc; Manrique, Daniel; Rodríguez-Patón, Alfonso; Sosík, Petr
2007-01-01
We present a P system with replicated rewriting to solve the Maximum Clique Problem for a graph. Strings representing cliques are built gradually. This involves the use of inhibitors that control the space of all generated solutions to the problem. Calculating the maximum clique for a graph is a highly relevant issue not only on purely computational grounds, but also because of its relationship to fundamental problems in genomics. We propose to implement the designed P system by means of a DNA algorithm. This algorithm is then compared with two standard papers that addressed the same problem and its DNA implementation in the past. This comparison is carried out on the basis of a series of computational and physical parameters. Our solution features a significantly lower cost in terms of time, the number and size of strands, as well as the simplicity of the biological implementation. PMID:17418940
ERIC Educational Resources Information Center
Karrison, Joan; Carroll, Margaret Kelly
1991-01-01
Students with language and learning disabilities may have difficulty solving mathematics word problems. Use of a sequential checklist, identifying clues and keywords, and illustrating a problem can all help the student identify and implement the correct computational process. (DB)
Teaching through Problem Solving
ERIC Educational Resources Information Center
Fi, Cos D.; Degner, Katherine M.
2012-01-01
Teaching through Problem Solving (TtPS) is an effective way to teach mathematics "for" understanding. It also provides students with a way to learn mathematics "with" understanding. In this article, the authors present a definition of what it means to teach through problem solving. They also describe a professional development vignette that…
ERIC Educational Resources Information Center
Karns, Phyllis Spear
The relationship of educational preparation to the problem- solving performance of 55 hospital employed baccalaureate and associate degree nurses working in Wyoming hospitals was studied. Participant data were collected that might correlate with problem-solving ability: age, years of experience in nursing, years of work experience in a…
Problem Solving and Intelligence.
ERIC Educational Resources Information Center
Resnick, Lauren B.; Glaser, Robert
This paper argues that a major aspect of intelligence is the ability to solve problems and that careful analysis of problem-solving behavior is a means of specifying many of the psychological processes that make up intelligence. The focus is on the mechanisms involved when, in the absence of complete instruction, a person must "invent" a new…
NASA Astrophysics Data System (ADS)
Xu, Ye; Wang, Ling; Wang, Shengyao; Liu, Min
2013-12-01
In this article, an effective shuffled frog-leaping algorithm (SFLA) is proposed to solve the hybrid flow-shop scheduling problem with identical parallel machines (HFSP-IPM). First, some novel heuristic decoding rules for both job order decision and machine assignment are proposed. Then, three hybrid decoding schemes are designed to decode job order sequences to schedules. A special bi-level crossover and multiple local search operators are incorporated in the searching framework of the SFLA to enrich the memetic searching behaviour and to balance the exploration and exploitation capabilities. Meanwhile, some theoretical analysis for the local search operators is provided for guiding the local search. The parameter setting of the algorithm is also investigated based on the Taguchi method of design of experiments. Finally, numerical testing based on well-known benchmarks and comparisons with some existing algorithms are carried out to demonstrate the effectiveness of the proposed algorithm.
NASA Astrophysics Data System (ADS)
Biswas, Papun; Chakraborti, Debjani
2010-10-01
This paper describes how the genetic algorithms (GAs) can be efficiently used to fuzzy goal programming (FGP) formulation of optimal power flow problems having multiple objectives. In the proposed approach, the different constraints, various relationships of optimal power flow calculations are fuzzily described. In the model formulation of the problem, the membership functions of the defined fuzzy goals are characterized first for measuring the degree of achievement of the aspiration levels of the goals specified in the decision making context. Then, the achievement function for minimizing the regret for under-deviations from the highest membership value (unity) of the defined membership goals to the extent possible on the basis of priorities is constructed for optimal power flow problems. In the solution process, the GA method is employed to the FGP formulation of the problem for achievement of the highest membership value (unity) of the defined membership functions to the extent possible in the decision making environment. In the GA based solution search process, the conventional Roulette wheel selection scheme, arithmetic crossover and random mutation are taken into consideration to reach a satisfactory decision. The developed method has been tested on IEEE 6-generator 30-bus System. Numerical results show that this method is promising for handling uncertain constraints in practical power systems.
ERIC Educational Resources Information Center
Capobianco, Brenda M.; Tyrie, Nancy
2009-01-01
In a unique school-university partnership, methods students collaborated with fifth graders to use the engineering design process to build their problem-solving skills. By placing the problem in the context of a client having particular needs, the problem took on a real-world appeal that students found intriguing and inviting. In this article, the…
Mathematics as Problem Solving.
ERIC Educational Resources Information Center
Soifer, Alexander
This book contains about 200 problems. It is suggested that it be used by students, teachers or anyone interested in exploring mathematics. In addition to a general discussion on problem solving, there are problems concerned with number theory, algebra, geometry, and combinatorics. (PK)
Chemical Reaction Problem Solving.
ERIC Educational Resources Information Center
Veal, William
1999-01-01
Discusses the role of chemical-equation problem solving in helping students predict reaction products. Methods for helping students learn this process must be taught to students and future teachers by using pedagogical skills within the content of chemistry. Emphasizes that solving chemical reactions should involve creative cognition where…
ERIC Educational Resources Information Center
Carpenter, Thomas P.; And Others
1980-01-01
Student weaknesses on problem-solving portions of the NAEP mathematics assessment are discussed using Polya's heuristics as a framework. Recommendations for classroom instruction are discussed. (MP) Aspect of National Assessment (NAEP) dealt with in this document: Results (Interpretation).
Solving Tommy's Writing Problems.
ERIC Educational Resources Information Center
Burdman, Debra
1986-01-01
The article describes an approach by which word processing helps to solve some of the writing problems of learning disabled students. Aspects considered include prewriting, drafting, revising, and completing the story. (CL)
ERIC Educational Resources Information Center
Martinez, Michael E.
1998-01-01
Many important human activities involve accomplishing goals without a script. There is no formula for true problem-solving. Heuristic, cognitive "rules of thumb" are the problem-solver's best guide. Learners should understand heuristic tools such as means-end analysis, working backwards, successive approximation, and external representation. Since…
ERIC Educational Resources Information Center
Thorson, Annette, Ed.
1999-01-01
This issue of ENC Focus focuses on the topic of inquiry and problem solving. Featured articles include: (1) "Inquiry in the Everyday World of Schools" (Ronald D. Anderson); (2) "In the Cascade Reservoir Restoration Project Students Tackle Real-World Problems" (Clint Kennedy with Advanced Biology Students from Cascade High School); (3) "Project…
Problem Solving Techniques Seminar.
ERIC Educational Resources Information Center
Massachusetts Career Development Inst., Springfield.
This booklet is one of six texts from a workplace literacy curriculum designed to assist learners in facing the increased demands of the workplace. Six problem-solving techniques are developed in the booklet to assist individuals and groups in making better decisions: problem identification, data gathering, data analysis, solution analysis,…
Problem Solving in Electricity.
ERIC Educational Resources Information Center
Caillot, Michel; Chalouhi, Elias
Two studies were conducted to describe how students perform direct current (D-C) circuit problems. It was hypothesized that problem solving in the electricity domain depends largely on good visual processing of the circuit diagram and that this processing depends on the ability to recognize when two or more electrical components are in series or…
NASA Technical Reports Server (NTRS)
1992-01-01
CBR Express software solves problems by adapting sorted solutions to new problems specified by a user. It is applicable to a wide range of situations. The technology was originally developed by Inference Corporation for Johnson Space Center's Advanced Software Development Workstation. The project focused on the reuse of software designs, and Inference used CBR as part of the ACCESS prototype software. The commercial CBR Express is used as a "help desk" for customer support, enabling reuse of existing information when necessary. It has been adopted by several companies, among them American Airlines, which uses it to solve reservation system software problems.
NASA Astrophysics Data System (ADS)
Heidari, A. A.; Kazemizade, O.; Abbaspour, R. A.
2015-12-01
In this paper, a continuous harmony search (HS) approach is investigated for tackling the Uncapacitated Facility Location (UFL) task. This article proposes an efficient modified HS-based optimizer to improve the performance of HS on complex spatial tasks like UFL problems. For this aim, opposition-based learning (OBL) and chaotic patterns are utilized. The proposed technique is examined against several UFL benchmark challenges in specialized literature. Then, the modified HS is substantiated in detail and compared to the basic HS and some other methods. The results showed that new opposition-based chaotic HS (OBCHS) algorithm not only can exploit better solutions competently but it is able to outperform HS in solving UFL problems.
ERIC Educational Resources Information Center
Wisconsin Univ. - Stout, Menomonie. Center for Vocational, Technical and Adult Education.
The teacher directed problem solving activities package contains 17 units: Future Community Design, Let's Build an Elevator, Let's Construct a Catapult, Let's Design a Recreational Game, Let's Make a Hand Fishing Reel, Let's Make a Wall Hanging, Let's Make a Yo-Yo, Marooned in the Past, Metrication, Mousetrap Vehicles, The Multi System…
ERIC Educational Resources Information Center
Aznar, Mercedes Martinez; Orcajo, Teresa Ibanez
2005-01-01
A teaching unit on genetics and human inheritance using problem-solving methodology was undertaken with fourth-level Spanish Secondary Education students (15 year olds). The goal was to study certain aspects of the students' learning process (concepts, procedures and attitude) when using this methodology in the school environment. The change…
Problem Solving Using Calculators.
ERIC Educational Resources Information Center
Billings, Karen; Moursund, David
1978-01-01
The first part in the serialized version of a book on the use of calculators for problem solving is presented. It contains prefaces for teachers and students and a chapter on getting started which includes topics such as symmetries, operations, powers, and chaining. (MP)
Solving Common Mathematical Problems
NASA Technical Reports Server (NTRS)
Luz, Paul L.
2005-01-01
Mathematical Solutions Toolset is a collection of five software programs that rapidly solve some common mathematical problems. The programs consist of a set of Microsoft Excel worksheets. The programs provide for entry of input data and display of output data in a user-friendly, menu-driven format, and for automatic execution once the input data has been entered.
Universal Design Problem Solving
ERIC Educational Resources Information Center
Sterling, Mary C.
2004-01-01
Universal design is made up of four elements: accessibility, adaptability, aesthetics, and affordability. This article addresses the concept of universal design problem solving through experiential learning for an interior design studio course in postsecondary education. Students' experiences with clients over age 55 promoted an understanding of…
ERIC Educational Resources Information Center
Moore, Jerilou; Sumrall, William J.
2008-01-01
Exploring our patent system is a great way to engage students in creative problem solving. As a result, the authors designed a teaching unit that uses the study of patents to explore one avenue in which scientists and engineers do science. Specifically, through the development of an idea, students learn how science and technology are connected.…
Solving Problems through Circles
ERIC Educational Resources Information Center
Grahamslaw, Laura; Henson, Lisa H.
2015-01-01
Several problem-solving interventions that utilise a "circle" approach have been applied within the field of educational psychology, for example, Circle Time, Circle of Friends, Sharing Circles, Circle of Adults and Solution Circles. This research explored two interventions, Solution Circles and Circle of Adults, and used thematic…
Circumference and Problem Solving.
ERIC Educational Resources Information Center
Blackburn, Katie; White, David
The concept of pi is one of great importance to all developed civilization and one that can be explored and mastered by elementary students through an inductive and problem-solving approach. Such an approach is outlined and discussed. The approach involves the following biblical quotation: "And he made a moltin sea ten cubits from one brim to the…
The Algorithm Selection Problem
NASA Technical Reports Server (NTRS)
Minton, Steve; Allen, John; Deiss, Ron (Technical Monitor)
1994-01-01
Work on NP-hard problems has shown that many instances of these theoretically computationally difficult problems are quite easy. The field has also shown that choosing the right algorithm for the problem can have a profound effect on the time needed to find a solution. However, to date there has been little work showing how to select the right algorithm for solving any particular problem. The paper refers to this as the algorithm selection problem. It describes some of the aspects that make this problem difficult, as well as proposes a technique for addressing it.
An algorithm for solving the system-level problem in multilevel optimization
NASA Technical Reports Server (NTRS)
Balling, R. J.; Sobieszczanski-Sobieski, J.
1994-01-01
A multilevel optimization approach which is applicable to nonhierarchic coupled systems is presented. The approach includes a general treatment of design (or behavior) constraints and coupling constraints at the discipline level through the use of norms. Three different types of norms are examined: the max norm, the Kreisselmeier-Steinhauser (KS) norm, and the 1(sub p) norm. The max norm is recommended. The approach is demonstrated on a class of hub frame structures which simulate multidisciplinary systems. The max norm is shown to produce system-level constraint functions which are non-smooth. A cutting-plane algorithm is presented which adequately deals with the resulting corners in the constraint functions. The algorithm is tested on hub frames with increasing number of members (which simulate disciplines), and the results are summarized.
NASA Astrophysics Data System (ADS)
Rajan, C. Christober Asir
2010-10-01
The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for the next H hours. Genetic Algorithms (GA's) are general-purpose optimization techniques based on principles inspired from the biological evolution using metaphors of mechanisms such as neural section, genetic recombination and survival of the fittest. In this, the unit commitment schedule is coded as a string of symbols. An initial population of parent solutions is generated at random. Here, each schedule is formed by committing all the units according to their initial status ("flat start"). Here the parents are obtained from a pre-defined set of solution's i.e. each and every solution is adjusted to meet the requirements. Then, a random recommitment is carried out with respect to the unit's minimum down times. And SA improves the status. A 66-bus utility power system with twelve generating units in India demonstrates the effectiveness of the proposed approach. Numerical results are shown comparing the cost solutions and computation time obtained by using the Genetic Algorithm method and other conventional methods.
Li, Kenli; Zou, Shuting; Xv, Jin
2008-01-01
Elliptic curve cryptographic algorithms convert input data to unrecognizable encryption and the unrecognizable data back again into its original decrypted form. The security of this form of encryption hinges on the enormous difficulty that is required to solve the elliptic curve discrete logarithm problem (ECDLP), especially over GF(2(n)), n in Z+. This paper describes an effective method to find solutions to the ECDLP by means of a molecular computer. We propose that this research accomplishment would represent a breakthrough for applied biological computation and this paper demonstrates that in principle this is possible. Three DNA-based algorithms: a parallel adder, a parallel multiplier, and a parallel inverse over GF(2(n)) are described. The biological operation time of all of these algorithms is polynomial with respect to n. Considering this analysis, cryptography using a public key might be less secure. In this respect, a principal contribution of this paper is to provide enhanced evidence of the potential of molecular computing to tackle such ambitious computations. PMID:18431451
NASA Astrophysics Data System (ADS)
Cram, Ana Catalina
As worldwide environmental awareness grow, alternative sources of energy have become important to mitigate climate change. Biogas in particular reduces greenhouse gas emissions that contribute to global warming and has the potential of providing 25% of the annual demand for natural gas in the U.S. In 2011, 55,000 metric tons of methane emissions were reduced and 301 metric tons of carbon dioxide emissions were avoided through the use of biogas alone. Biogas is produced by anaerobic digestion through the fermentation of organic material. It is mainly composed of methane with a rage of 50 to 80% in its concentration. Carbon dioxide covers 20 to 50% and small amounts of hydrogen, carbon monoxide and nitrogen. The biogas production systems are anaerobic digestion facilities and the optimal operation of an anaerobic digester requires the scheduling of all batches from multiple feedstocks during a specific time horizon. The availability times, biomass quantities, biogas production rates and storage decay rates must all be taken into account for maximal biogas production to be achieved during the planning horizon. Little work has been done to optimize the scheduling of different types of feedstock in anaerobic digestion facilities to maximize the total biogas produced by these systems. Therefore, in the present thesis, a new genetic algorithm is developed with the main objective of obtaining the optimal sequence in which different feedstocks will be processed and the optimal time to allocate to each feedstock in the digester with the main objective of maximizing the production of biogas considering different types of feedstocks, arrival times and decay rates. Moreover, all batches need to be processed in the digester in a specified time with the restriction that only one batch can be processed at a time. The developed algorithm is applied to 3 different examples and a comparison with results obtained in previous studies is presented.
Cristofolini, Andrea; Latini, Chiara; Borghi, Carlo A.
2011-02-01
This paper presents a technique for improving the convergence rate of a generalized minimum residual (GMRES) algorithm applied for the solution of a algebraic system produced by the discretization of an electrodynamic problem with a tensorial electrical conductivity. The electrodynamic solver considered in this work is a part of a magnetohydrodynamic (MHD) code in the low magnetic Reynolds number approximation. The code has been developed for the analysis of MHD interaction during the re-entry phase of a space vehicle. This application is a promising technique intensively investigated for the shock mitigation and the vehicle control in the higher layers of a planetary atmosphere. The medium in the considered application is a low density plasma, characterized by a tensorial conductivity. This is a result of the behavior of the free electric charges, which tend to drift in a direction perpendicular both to the electric field and to the magnetic field. In the given approximation, the electrodynamics is described by an elliptical partial differential equation, which is solved by means of a finite element approach. The linear system obtained by discretizing the problem is solved by means of a GMRES iterative method with an incomplete LU factorization threshold preconditioning. The convergence of the solver appears to be strongly affected by the tensorial characteristic of the conductivity. In order to deal with this feature, the bandwidth reduction in the coefficient matrix is considered and a novel technique is proposed and discussed. First, the standard reverse Cuthill-McKee (RCM) procedure has been applied to the problem. Then a modification of the RCM procedure (the weighted RCM procedure, WRCM) has been developed. In the last approach, the reordering is performed taking into account the relation between the mesh geometry and the magnetic field direction. In order to investigate the effectiveness of the methods, two cases are considered. The RCM and WRCM procedures
Computer Problem-Solving Coaches
NASA Astrophysics Data System (ADS)
Hsu, Leon; Heller, Kenneth
2005-09-01
Computers might be able to play an important role in physics instruction by coaching students to develop good problem-solving skills. Building on previous research on student problem solving and on designing computer programs to teach cognitive skills, we are developing a prototype computer coach to provide students with guided practice in solving problems. In addition to helping students become better problem solvers, such programs can be useful in studying how students learn to solve problems and how and if problem-solving skills can be transferred from a computer to a pencil-and-paper environment.
The Problem-Solving Revolution.
ERIC Educational Resources Information Center
Bardige, Art
1983-01-01
Discusses the use of microcomputers and software as problem-solving tools, including comments on "TK! Solver," automatic problem-solving program (reviewed in detail on pp.84-86 in this same issue). Also discusses problem-solving approaches to bridge the disciplines, such as music/physics, junior high science/mathematics (genetics),…
The Identity of Problem Solving
ERIC Educational Resources Information Center
Mamona-Downs, Joanna; Downs, Martin
2005-01-01
This paper raises issues motivated by considering the "identity" of problem solving. This means that we are concerned with how other mathematics education topics impinge on problem solving, and with themes that naturally arise within the problem-solving agenda. We claim that some of these issues need more attention by educational research, while…
ERIC Educational Resources Information Center
Gultepe, Nejla; Yalcin Celik, Ayse; Kilic, Ziya
2013-01-01
The purpose of the study was to examine the effects of students' conceptual understanding of chemical concepts and mathematical processing skills on algorithmic problem-solving skills. The sample (N = 554) included grades 9, 10, and 11 students in Turkey. Data were collected using the instrument "MPC Test" and with interviews. The…
Solving global optimization problems on GPU cluster
NASA Astrophysics Data System (ADS)
Barkalov, Konstantin; Gergel, Victor; Lebedev, Ilya
2016-06-01
The paper contains the results of investigation of a parallel global optimization algorithm combined with a dimension reduction scheme. This allows solving multidimensional problems by means of reducing to data-independent subproblems with smaller dimension solved in parallel. The new element implemented in the research consists in using several graphic accelerators at different computing nodes. The paper also includes results of solving problems of well-known multiextremal test class GKLS on Lobachevsky supercomputer using tens of thousands of GPU cores.
NASA Astrophysics Data System (ADS)
Fernández Martínez, Juan L.; García Gonzalo, Esperanza; Fernández Álvarez, José P.; Kuzma, Heidi A.; Menéndez Pérez, César O.
2010-05-01
PSO is an optimization technique inspired by the social behavior of individuals in nature (swarms) that has been successfully used in many different engineering fields. In addition, the PSO algorithm can be physically interpreted as a stochastic damped mass-spring system. This analogy has served to introduce the PSO continuous model and to deduce a whole family of PSO algorithms using different finite-differences schemes. These algorithms are characterized in terms of convergence by their respective first and second order stability regions. The performance of these new algorithms is first checked using synthetic functions showing a degree of ill-posedness similar to that found in many geophysical inverse problems having their global minimum located on a very narrow flat valley or surrounded by multiple local minima. Finally we present the application of these PSO algorithms to the analysis and solution of a VES inverse problem associated with a seawater intrusion in a coastal aquifer in southern Spain. PSO family members are successfully compared to other well known global optimization algorithms (binary genetic algorithms and simulated annealing) in terms of their respective convergence curves and the sea water intrusion depth posterior histograms.
A Method for Solving Problems.
ERIC Educational Resources Information Center
Knoop, Robert
1987-01-01
Problem solving and decision making are considered to be keys to successful management. A normative method for problem solving is presented, suggesting that the analysis of the problem be structured along a five-step procedure: problem identification, analysis, decision alternatives, decision making, and decision implementation. Follow-up…
ERIC Educational Resources Information Center
Niaz, Mansoor
The main objective of this study is to construct models based on strategies students use to solve chemistry problems and to show that these models form sequences of progressive transitions similar to what Lakatos (1970) in the history of science refers to as progressive 'problemshifts' that increase the explanatory' heuristic power of the models.…
ERIC Educational Resources Information Center
Tsaparlis, Georgios
2005-01-01
This work provides a correlation study of the role of the following cognitive variables on problem solving in elementary physical chemistry: scientific reasoning (level of intellectual development/developmental level), working-memory capacity, functional mental ("M") capacity, and disembedding ability (i.e., degree of perceptual field…
Zhang, Weizhe; Bai, Enci; He, Hui; Cheng, Albert M.K.
2015-01-01
Reducing energy consumption is becoming very important in order to keep battery life and lower overall operational costs for heterogeneous real-time multiprocessor systems. In this paper, we first formulate this as a combinatorial optimization problem. Then, a successful meta-heuristic, called Shuffled Frog Leaping Algorithm (SFLA) is proposed to reduce the energy consumption. Precocity remission and local optimal avoidance techniques are proposed to avoid the precocity and improve the solution quality. Convergence acceleration significantly reduces the search time. Experimental results show that the SFLA-based energy-aware meta-heuristic uses 30% less energy than the Ant Colony Optimization (ACO) algorithm, and 60% less energy than the Genetic Algorithm (GA) algorithm. Remarkably, the running time of the SFLA-based meta-heuristic is 20 and 200 times less than ACO and GA, respectively, for finding the optimal solution. PMID:26110406
Zhang, Weizhe; Bai, Enci; He, Hui; Cheng, Albert M K
2015-01-01
Reducing energy consumption is becoming very important in order to keep battery life and lower overall operational costs for heterogeneous real-time multiprocessor systems. In this paper, we first formulate this as a combinatorial optimization problem. Then, a successful meta-heuristic, called Shuffled Frog Leaping Algorithm (SFLA) is proposed to reduce the energy consumption. Precocity remission and local optimal avoidance techniques are proposed to avoid the precocity and improve the solution quality. Convergence acceleration significantly reduces the search time. Experimental results show that the SFLA-based energy-aware meta-heuristic uses 30% less energy than the Ant Colony Optimization (ACO) algorithm, and 60% less energy than the Genetic Algorithm (GA) algorithm. Remarkably, the running time of the SFLA-based meta-heuristic is 20 and 200 times less than ACO and GA, respectively, for finding the optimal solution. PMID:26110406
Problem Solving: Can Anybody Do It?
ERIC Educational Resources Information Center
Bennett, Stuart W.
2008-01-01
This paper examines the definition of a problem and at the process of problem solving. An analysis of a number of first and third year chemistry examination papers from English universities revealed that over ninety per cent of the "problems" fell into the "algorithm" category. Using Bloom's taxonomy and the same examination papers, we found that…
McHugh, P.R.
1995-10-01
Fully coupled, Newton-Krylov algorithms are investigated for solving strongly coupled, nonlinear systems of partial differential equations arising in the field of computational fluid dynamics. Primitive variable forms of the steady incompressible and compressible Navier-Stokes and energy equations that describe the flow of a laminar Newtonian fluid in two-dimensions are specifically considered. Numerical solutions are obtained by first integrating over discrete finite volumes that compose the computational mesh. The resulting system of nonlinear algebraic equations are linearized using Newton`s method. Preconditioned Krylov subspace based iterative algorithms then solve these linear systems on each Newton iteration. Selected Krylov algorithms include the Arnoldi-based Generalized Minimal RESidual (GMRES) algorithm, and the Lanczos-based Conjugate Gradients Squared (CGS), Bi-CGSTAB, and Transpose-Free Quasi-Minimal Residual (TFQMR) algorithms. Both Incomplete Lower-Upper (ILU) factorization and domain-based additive and multiplicative Schwarz preconditioning strategies are studied. Numerical techniques such as mesh sequencing, adaptive damping, pseudo-transient relaxation, and parameter continuation are used to improve the solution efficiency, while algorithm implementation is simplified using a numerical Jacobian evaluation. The capabilities of standard Newton-Krylov algorithms are demonstrated via solutions to both incompressible and compressible flow problems. Incompressible flow problems include natural convection in an enclosed cavity, and mixed/forced convection past a backward facing step.
NASA Technical Reports Server (NTRS)
Loewenstein, M.; Greenblatt. B. J.; Jost, H.; Podolske, J. R.; Elkins, Jim; Hurst, Dale; Romanashkin, Pavel; Atlas, Elliott; Schauffler, Sue; Donnelly, Steve; Condon, Estelle (Technical Monitor)
2000-01-01
De-nitrification and excess re-nitrification was widely observed by ER-2 instruments in the Arctic vortex during SOLVE in winter/spring 2000. Analyses of these events requires a knowledge of the initial or pre-vortex state of the sampled air masses. The canonical relationship of NOy to the long-lived tracer N2O observed in the unperturbed stratosphere is generally used for this purpose. In this paper we will attempt to establish the current unperturbed NOy:N2O relationship (NOy* algorithm) using the ensemble of extra-vortex data from in situ instruments flying on the ER-2 and DC-8, and from the Mark IV remote measurements on the OMS balloon. Initial analysis indicates a change in the SOLVE NOy* from the values predicted by the 1994 Northern Hemisphere NOy* algorithm which was derived from the observations in the ASHOE/MAESA campaign.
Parent Problem Solving: Analysis of Problem Solving in Parenthood Transition.
ERIC Educational Resources Information Center
Alpert, Judith L.; And Others
The general purpose of this study was to explore the possibility of adapting the Means-Ends Problem-Solving procedure (MEPS) to the investigation of the individual's transition to parenthood. Specific purposes were to determine (1) the internal consistency of the Parent Problem-Solving Scale (PPSS), of its subclasses, and of a combined subscale;…
Robot computer problem solving system
NASA Technical Reports Server (NTRS)
Merriam, E. W.; Becker, J. D.
1973-01-01
A robot computer problem solving system which represents a robot exploration vehicle in a simulated Mars environment is described. The model exhibits changes and improvements made on a previously designed robot in a city environment. The Martian environment is modeled in Cartesian coordinates; objects are scattered about a plane; arbitrary restrictions on the robot's vision have been removed; and the robot's path contains arbitrary curves. New environmental features, particularly the visual occlusion of objects by other objects, were added to the model. Two different algorithms were developed for computing occlusion. Movement and vision capabilities of the robot were established in the Mars environment, using LISP/FORTRAN interface for computational efficiency. The graphical display program was redesigned to reflect the change to the Mars-like environment.
Problem Solving vis Soap Bubbles
ERIC Educational Resources Information Center
Bader, William A.
1975-01-01
Describes the use of a scientific phenomenon related to the concept of surface tension as an intriguing vehicle to direct attention to useful problem solving techniques. The need for a definite building process in attempts to solve mathematical problems is stressed. (EB)
Contextual Problem Solving Model Origination
ERIC Educational Resources Information Center
Ernst, Jeremy V.
2009-01-01
Problem solving has become a central focus of instructional activity in technology education classrooms at all levels (Boser, 1993). Impact assessment considerations incorporating society, culture, and economics are factors that require high-level deliberation involving critical thinking and the implementation of problem solving strategy. The…
Difficulties in Genetics Problem Solving.
ERIC Educational Resources Information Center
Tolman, Richard R.
1982-01-01
Examined problem-solving strategies of 30 high school students as they solved genetics problems. Proposes a new sequence of teaching genetics based on results: meiosis, sex chromosomes, sex determination, sex-linked traits, monohybrid and dihybrid crosses (humans), codominance (humans), and Mendel's pea experiments. (JN)
Learning Impasses in Problem Solving
NASA Technical Reports Server (NTRS)
Hodgson, J. P. E.
1992-01-01
Problem Solving systems customarily use backtracking to deal with obstacles that they encounter in the course of trying to solve a problem. This paper outlines an approach in which the possible obstacles are investigated prior to the search for a solution. This provides a solution strategy that avoids backtracking.
Problem Solving, Scaffolding and Learning
ERIC Educational Resources Information Center
Lin, Shih-Yin
2012-01-01
Helping students to construct robust understanding of physics concepts and develop good solving skills is a central goal in many physics classrooms. This thesis examine students' problem solving abilities from different perspectives and explores strategies to scaffold students' learning. In studies involving analogical problem solving…
Creative Thinking and Problem Solving.
ERIC Educational Resources Information Center
Lacy, Grace
The booklet considers the nature of creativity in children and examines classroom implications. Among the topics addressed are the following: theories about creativity; research; developments in brain research; the creative process; creative problem solving; the Structure of Intellect Problem Solving (SIPS) model; a rationale for creativity in the…
Learning through Problem Solving.
ERIC Educational Resources Information Center
Murray, Hanlie; Olivier, Alwyn; Human, Piet
After conducting several studies on young students' understanding of particular concepts before, during, and after instruction, this paper focuses on the two small scale and several informal teaching experiments based on the idea that the teacher should pose problems to students for which they do not yet have a routine solution method available,…
Transformation Problem Solving Abilities.
ERIC Educational Resources Information Center
Harmel, Sarah Jane
The relationship between transformation problem performance and Guilford Structure of Intellect (SI) abilities is explored. During two group sessions 42 females and 35 males, age 18-39, were administered 12 Guilford SI tests exemplifying all five symbolic content (numeric) operations, and three contents in the divergent production area. Logical…
ERIC Educational Resources Information Center
De Bono, Edward
A group of children were presented with several tasks, including the invention of a sleep machine and a machine to weigh elephants. The tasks were chosen to involve the children in coping with problems of a distinct character. A study of the children's drawings and interpretations shows that children's thinking ability is not very different from…
Solving bearing overheating problems
Jendzurski, T.
1995-05-08
Overheating is a major indicator, along with vibration and noise, of an underlying problem affecting a bearing or related components. Because normal operating temperatures vary widely from one application to another, no single temperature is a reliable sign of overheating in every situation. By observing an application when it is running smoothly, a technician can establish a benchmark temperature for a particular bearing arrangement. Wide deviations from this accepted norm generally indicate troublesome overheating. The list of possible causes of over-heating ranges from out-of-round housings and oversize shaft diameters to excessive lubrication and bearing preloading. These causes fall into two major categories: improper or faulty lubrication and mechanical problems, such as incorrect fits and tolerances. These are discussed along with solutions.
Irrelevance in Problem Solving
NASA Technical Reports Server (NTRS)
Levy, Alon Y.
1992-01-01
The notion of irrelevance underlies many different works in AI, such as detecting redundant facts, creating abstraction hierarchies and reformulation and modeling physical devices. However, in order to design problem solvers that exploit the notion of irrelevance, either by automatically detecting irrelevance or by being given knowledge about irrelevance, a formal treatment of the notion is required. In this paper we present a general framework for analyzing irrelevance. We discuss several properties of irrelevance and show how they vary in a space of definitions outlined by the framework. We show how irrelevance claims can be used to justify the creation of abstractions thereby suggesting a new view on the work on abstraction.
Supporting Problem Solving in PBL
ERIC Educational Resources Information Center
Jonassen, David
2011-01-01
Although the characteristics of PBL (problem focused, student centered, self-directed, etc.) are well known, the components of a problem-based learning environment (PBLE) and the cognitive scaffolds necessary to support learning to solve different kinds of problems with different learners is less clear. This paper identifies the different…
Solving multiconstraint assignment problems using learning automata.
Horn, Geir; Oommen, B John
2010-02-01
This paper considers the NP-hard problem of object assignment with respect to multiple constraints: assigning a set of elements (or objects) into mutually exclusive classes (or groups), where the elements which are "similar" to each other are hopefully located in the same class. The literature reports solutions in which the similarity constraint consists of a single index that is inappropriate for the type of multiconstraint problems considered here and where the constraints could simultaneously be contradictory. This feature, where we permit possibly contradictory constraints, distinguishes this paper from the state of the art. Indeed, we are aware of no learning automata (or other heuristic) solutions which solve this problem in its most general setting. Such a scenario is illustrated with the static mapping problem, which consists of distributing the processes of a parallel application onto a set of computing nodes. This is a classical and yet very important problem within the areas of parallel computing, grid computing, and cloud computing. We have developed four learning-automata (LA)-based algorithms to solve this problem: First, a fixed-structure stochastic automata algorithm is presented, where the processes try to form pairs to go onto the same node. This algorithm solves the problem, although it requires some centralized coordination. As it is desirable to avoid centralized control, we subsequently present three different variable-structure stochastic automata (VSSA) algorithms, which have superior partitioning properties in certain settings, although they forfeit some of the scalability features of the fixed-structure algorithm. All three VSSA algorithms model the processes as automata having first the hosting nodes as possible actions; second, the processes as possible actions; and, third, attempting to estimate the process communication digraph prior to probabilistically mapping the processes. This paper, which, we believe, comprehensively reports the
Problem Solving with General Semantics.
ERIC Educational Resources Information Center
Hewson, David
1996-01-01
Discusses how to use general semantics formulations to improve problem solving at home or at work--methods come from the areas of artificial intelligence/computer science, engineering, operations research, and psychology. (PA)
AI tools in computer based problem solving
NASA Technical Reports Server (NTRS)
Beane, Arthur J.
1988-01-01
The use of computers to solve value oriented, deterministic, algorithmic problems, has evolved a structured life cycle model of the software process. The symbolic processing techniques used, primarily in research, for solving nondeterministic problems, and those for which an algorithmic solution is unknown, have evolved a different model, much less structured. Traditionally, the two approaches have been used completely independently. With the advent of low cost, high performance 32 bit workstations executing identical software with large minicomputers and mainframes, it became possible to begin to merge both models into a single extended model of computer problem solving. The implementation of such an extended model on a VAX family of micro/mini/mainframe systems is described. Examples in both development and deployment of applications involving a blending of AI and traditional techniques are given.
Problem Solving through Paper Folding
ERIC Educational Resources Information Center
Wares, Arsalan
2014-01-01
The purpose of this article is to describe a couple of challenging mathematical problems that involve paper folding. These problem-solving tasks can be used to foster geometric and algebraic thinking among students. The context of paper folding makes some of the abstract mathematical ideas involved relatively concrete. When implemented…
Quantitative Reasoning in Problem Solving
ERIC Educational Resources Information Center
Ramful, Ajay; Ho, Siew Yin
2015-01-01
In this article, Ajay Ramful and Siew Yin Ho explain the meaning of quantitative reasoning, describing how it is used in the to solve mathematical problems. They also describe a diagrammatic approach to represent relationships among quantities and provide examples of problems and their solutions.
Students' Problem Solving and Justification
ERIC Educational Resources Information Center
Glass, Barbara; Maher, Carolyn A.
2004-01-01
This paper reports on methods of students' justifications of their solution to a problem in the area of combinatorics. From the analysis of the problem solving of 150 students in a variety of settings from high-school to graduate study, four major forms of reasoning evolved: (1) Justification by Cases, (2) Inductive Argument, (3) Elimination…
Robot, computer problem solving system
NASA Technical Reports Server (NTRS)
Becker, J. D.
1972-01-01
The development of a computer problem solving system is reported that considers physical problems faced by an artificial robot moving around in a complex environment. Fundamental interaction constraints with a real environment are simulated for the robot by visual scan and creation of an internal environmental model. The programming system used in constructing the problem solving system for the simulated robot and its simulated world environment is outlined together with the task that the system is capable of performing. A very general framework for understanding the relationship between an observed behavior and an adequate description of that behavior is included.
Computer Enhanced Problem Solving Skill Acquisition.
ERIC Educational Resources Information Center
Slotnick, Robert S.
1989-01-01
Discusses the implementation of interactive educational software that was designed to enhance critical thinking, scientific reasoning, and problem solving in a university psychology course. Piagetian and computer learning perspectives are explained; the courseware package, PsychWare, is described; and the use of heuristics and algorithms in…
Problem? "No Problem!" Solving Technical Contradictions
ERIC Educational Resources Information Center
Kutz, K. Scott; Stefan, Victor
2007-01-01
TRIZ (pronounced TREES), the Russian acronym for the theory of inventive problem solving, enables a person to focus his attention on finding genuine, potential solutions in contrast to searching for ideas that "may" work through a happenstance way. It is a patent database-backed methodology that helps to reduce time spent on the problem,…
Quantum Computing: Solving Complex Problems
DiVincenzo, David [IBM Watson Research Center
2009-09-01
One of the motivating ideas of quantum computation was that there could be a new kind of machine that would solve hard problems in quantum mechanics. There has been significant progress towards the experimental realization of these machines (which I will review), but there are still many questions about how such a machine could solve computational problems of interest in quantum physics. New categorizations of the complexity of computational problems have now been invented to describe quantum simulation. The bad news is that some of these problems are believed to be intractable even on a quantum computer, falling into a quantum analog of the NP class. The good news is that there are many other new classifications of tractability that may apply to several situations of physical interest.
Quantum Computing: Solving Complex Problems
DiVincenzo, David
2007-04-12
One of the motivating ideas of quantum computation was that there could be a new kind of machine that would solve hard problems in quantum mechanics. There has been significant progress towards the experimental realization of these machines (which I will review), but there are still many questions about how such a machine could solve computational problems of interest in quantum physics. New categorizations of the complexity of computational problems have now been invented to describe quantum simulation. The bad news is that some of these problems are believed to be intractable even on a quantum computer, falling into a quantum analog of the NP class. The good news is that there are many other new classifications of tractability that may apply to several situations of physical interest.
Quantum Computing: Solving Complex Problems
DiVincenzo, David
2007-04-11
One of the motivating ideas of quantum computation was that there could be a new kind of machine that would solve hard problems in quantum mechanics. There has been significant progress towards the experimental realization of these machines (which I will review), but there are still many questions about how such a machine could solve computational problems of interest in quantum physics. New categorizations of the complexity of computational problems have now been invented to describe quantum simulation. The bad news is that some of these problems are believed to be intractable even on a quantum computer, falling into a quantum analog of the NP class. The good news is that there are many other new classifications of tractability that may apply to several situations of physical interest.
Doha, E.H.; Abd-Elhameed, W.M.; Youssri, Y.H.
2014-01-01
Two families of certain nonsymmetric generalized Jacobi polynomials with negative integer indexes are employed for solving third- and fifth-order two point boundary value problems governed by homogeneous and nonhomogeneous boundary conditions using a dual Petrov–Galerkin method. The idea behind our method is to use trial functions satisfying the underlying boundary conditions of the differential equations and the test functions satisfying the dual boundary conditions. The resulting linear systems from the application of our method are specially structured and they can be efficiently inverted. The use of generalized Jacobi polynomials simplify the theoretical and numerical analysis of the method and also leads to accurate and efficient numerical algorithms. The presented numerical results indicate that the proposed numerical algorithms are reliable and very efficient. PMID:26425358
Al Nasr, Kamal; Ranjan, Desh; Zubair, Mohammad; Chen, Lin; He, Jing
2014-01-01
Electron cryomicroscopy is becoming a major experimental technique in solving the structures of large molecular assemblies. More and more three-dimensional images have been obtained at the medium resolutions between 5 and 10 Å. At this resolution range, major α-helices can be detected as cylindrical sticks and β-sheets can be detected as plain-like regions. A critical question in de novo modeling from cryo-EM images is to determine the match between the detected secondary structures from the image and those on the protein sequence. We formulate this matching problem into a constrained graph problem and present an O(Δ(2)N(2)2(N)) algorithm to this NP-Hard problem. The algorithm incorporates the dynamic programming approach into a constrained K-shortest path algorithm. Our method, DP-TOSS, has been tested using α-proteins with maximum 33 helices and α-β proteins up to five helices and 12 β-strands. The correct match was ranked within the top 35 for 19 of the 20 α-proteins and all nine α-β proteins tested. The results demonstrate that DP-TOSS improves accuracy, time and memory space in deriving the topologies of the secondary structure elements for proteins with a large number of secondary structures and a complex skeleton. PMID:26355788
Robot computer problem solving system
NASA Technical Reports Server (NTRS)
Becker, J. D.; Merriam, E. W.
1974-01-01
The conceptual, experimental, and practical aspects of the development of a robot computer problem solving system were investigated. The distinctive characteristics were formulated of the approach taken in relation to various studies of cognition and robotics. Vehicle and eye control systems were structured, and the information to be generated by the visual system is defined.
Solving Problems by Reading Mathematics.
ERIC Educational Resources Information Center
Witkowski, Joseph C.
1988-01-01
A course at the University of Georgia is described that helps students acquire problem-solving skills so that ultimately the entire remedial program would be improved, giving students with major deficiencies in basic skills a better chance to succeed in their regular university courses. (MLW)
Robot computer problem solving system
NASA Technical Reports Server (NTRS)
Becker, J. D.; Merriam, E. W.
1974-01-01
The conceptual, experimental, and practical phases of developing a robot computer problem solving system are outlined. Robot intelligence, conversion of the programming language SAIL to run under the THNEX monitor, and the use of the network to run several cooperating jobs at different sites are discussed.
ERIC Educational Resources Information Center
Champagne, Audrey B.; And Others
Teachers in elementary schools, supervisors of instruction, and other educational practitioners are the primary audience for this publication. The paper presents philosophical, psychological, and practical reasons for including a problem-solving approach in elementary school instruction. It draws on the writings of John Dewey, Jean Piaget, James…
Customer Service & Team Problem Solving.
ERIC Educational Resources Information Center
Martin, Sabrina Budasi
This curriculum guide provides materials for a six-session, site-specific training course in customer service and team problem solving for the Claretian Medical Center. The course outline is followed the six lesson plans. Components of each lesson plan include a list of objectives, an outline of activities and discussion topics for the lesson,…
Toward a Comprehensive Model of Problem-Solving.
ERIC Educational Resources Information Center
Pitt, Ruth B.
Presented is a model of problem solving that incorporates elements of hypothetico-deductive reasoning in the Piagetian sense, and heuristic-algorithmic processing in the information-processing sense. It assumes that people invoke both formal reasoning strategies and learned algorithms whenever they solve problems. The proposed model integrates the…
Genetics problem solving and worldview
NASA Astrophysics Data System (ADS)
Dale, Esther
The research goal was to determine whether worldview relates to traditional and real-world genetics problem solving. Traditionally, scientific literacy emphasized content knowledge alone because it was sufficient to solve traditional problems. The contemporary definition of scientific literacy is, "The knowledge and understanding of scientific concepts and processes required for personal decision-making, participation in civic and cultural affairs and economic productivity" (NRC, 1996). An expanded definition of scientific literacy is needed to solve socioscientific issues (SSI), complex social issues with conceptual, procedural, or technological associations with science. Teaching content knowledge alone assumes that students will find the scientific explanation of a phenomenon to be superior to a non-science explanation. Formal science and everyday ways of thinking about science are two different cultures (Palmer, 1999). Students address this rift with cognitive apartheid, the boxing away of science knowledge from other types of knowledge (Jedege & Aikenhead, 1999). By addressing worldview, cognitive apartheid may decrease and scientific literacy may increase. Introductory biology students at the University of Minnesota during fall semester 2005 completed a written questionnaire-including a genetics content-knowledge test, four genetic dilemmas, the Worldview Assessment Instrument (WAI) and some items about demographics and religiosity. Six students responded to the interview protocol. Based on statistical analysis and interview data, this study concluded the following: (1) Worldview, in the form of metaphysics, relates to solving traditional genetic dilemmas. (2) Worldview, in the form of agency, relates to solving traditional genetics problems. (3) Thus, worldview must be addressed in curriculum, instruction, and assessment.
Solving combinatorial problems: the 15-puzzle.
Pizlo, Zygmunt; Li, Zheng
2005-09-01
We present a series of experiments in which human subjects were tested with a well-known combinatorial problem called the 15-puzzle and in different-sized variants of this puzzle. Subjects can solve these puzzles reliably by systematically building a solution path, without performing much search and without using distances among the states of the problem. The computational complexity of the underlying mental mechanisms is very low. We formulated a computational model of the underlying cognitive processes on the basis of our results. This model applied a pyramid algorithm to individual stages of each problem. The model's performance proved to be quite similar to the subjects' performance. PMID:16496727
Modeling Applied to Problem Solving
NASA Astrophysics Data System (ADS)
Pawl, Andrew; Barrantes, Analia; Pritchard, David E.
2009-11-01
We describe a modeling approach to help students learn expert problem solving. Models are used to present and hierarchically organize the syllabus content and apply it to problem solving, but students do not develop and validate their own Models through guided discovery. Instead, students classify problems under the appropriate instructor-generated Model by selecting a system to consider and describing the interactions that are relevant to that system. We believe that this explicit System, Interactions and Model (S.I.M.) problem modeling strategy represents a key simplification and clarification of the widely disseminated modeling approach originated by Hestenes and collaborators. Our narrower focus allows modeling physics to be integrated into (as opposed to replacing) a typical introductory college mechanics course, while preserving the emphasis on understanding systems and interactions that is the essence of modeling. We have employed the approach in a three-week review course for MIT freshmen who received a D in the fall mechanics course with very encouraging results.
Journey toward Teaching Mathematics through Problem Solving
ERIC Educational Resources Information Center
Sakshaug, Lynae E.; Wohlhuter, Kay A.
2010-01-01
Teaching mathematics through problem solving is a challenge for teachers who learned mathematics by doing exercises. How do teachers develop their own problem solving abilities as well as their abilities to teach mathematics through problem solving? A group of teachers began the journey of learning to teach through problem solving while taking a…
Problem Solving in the Context of Medicine.
ERIC Educational Resources Information Center
Woods, Donald R.
1997-01-01
Reviews the book "Medical Problem Solving: An Analysis of Clinical Reasoning," a seminal book whose conclusions on problem solving in medical fields are still valid today. Discusses major problem-solving findings of this book, the application of the findings to education, and relating knowledge to problem-solving skills. (JRH)
Solving the Dark Matter Problem
Baltz, Ted
2009-09-01
Cosmological observations have firmly established that the majority of matter in the universe is of an unknown type, called 'dark matter'. A compelling hypothesis is that the dark matter consists of weakly interacting massive particles (WIMPs) in the mass range around 100 GeV. If the WIMP hypothesis is correct, such particles could be created and studied at accelerators. Furthermore they could be directly detected as the primary component of our galaxy. Solving the dark matter problem requires that the connection be made between the two. We describe some theoretical and experimental avenues that might lead to this connection.
Theoretical and Philosophical Perspectives to Problem Solving.
ERIC Educational Resources Information Center
Sherman, Thomas M.; And Others
1988-01-01
Five articles explore various theoretical aspects of problems and problem solving skills. Highlights include strategies to learn problem solving skills; knowledge structures; metacognition; behavioral processes and cognitive psychology; erotetic logic; creativity as an aspect of computer problem solving; and programing as a problem-solving…
Research on Computers and Problem Solving.
ERIC Educational Resources Information Center
Burton, John K.; And Others
1988-01-01
Eight articles review and report on research involving computers and problem solving skills. Topics discussed include research design; problem solving skills and programing languages, including BASIC and LOGO; computer anxiety; diagnostic programs for arithmetic problems; and relationships between ability and problem solving scores and between…
King Oedipus and the Problem Solving Process.
ERIC Educational Resources Information Center
Borchardt, Donald A.
An analysis of the problem solving process reveals at least three options: (1) finding the cause, (2) solving the problem, and (3) anticipating potential problems. These methods may be illustrated by examining "Oedipus Tyrannus," a play in which a king attempts to deal with a problem that appears to be beyond his ability to solve, and applying…
Disciplinary Foundations for Solving Interdisciplinary Scientific Problems
ERIC Educational Resources Information Center
Zhang, Dongmei; Shen, Ji
2015-01-01
Problem-solving has been one of the major strands in science education research. But much of the problem-solving research has been conducted on discipline-based contexts; little research has been done on how students, especially individuals, solve interdisciplinary problems. To understand how individuals reason about interdisciplinary problems, we…
Exploiting Quantum Resonance to Solve Combinatorial Problems
NASA Technical Reports Server (NTRS)
Zak, Michail; Fijany, Amir
2006-01-01
Quantum resonance would be exploited in a proposed quantum-computing approach to the solution of combinatorial optimization problems. In quantum computing in general, one takes advantage of the fact that an algorithm cannot be decoupled from the physical effects available to implement it. Prior approaches to quantum computing have involved exploitation of only a subset of known quantum physical effects, notably including parallelism and entanglement, but not including resonance. In the proposed approach, one would utilize the combinatorial properties of tensor-product decomposability of unitary evolution of many-particle quantum systems for physically simulating solutions to NP-complete problems (a class of problems that are intractable with respect to classical methods of computation). In this approach, reinforcement and selection of a desired solution would be executed by means of quantum resonance. Classes of NP-complete problems that are important in practice and could be solved by the proposed approach include planning, scheduling, search, and optimal design.
Community-powered problem solving.
Gouillart, Francis; Billings, Douglas
2013-04-01
Traditionally, companies have managed their constituencies with specific processes: marketing to customers, procuring from vendors, developing HR policies for employees, and so on. The problem is, such processes focus on repeatability and compliance, so they can lead to stagnation. Inviting your constituencies to collectively help you solve problems and exploit opportunities--"co-creation"--is a better approach. It allows you to continually tap the skills and insights of huge numbers of stakeholders and develop new ways to produce value for all. The idea is to provide stakeholders with platforms (physical and digital forums) on which they can interact, get them to start exploring new experiences and connections, and let the system grow organically. A co-creation initiative by a unit of Becton, Dickinson and Company demonstrates how this works. A global leader in syringes, BD set out to deepen its ties with hospital customers and help them reduce the incidence of infections from unsafe injection and syringe disposal practices. The effort began with a cross-functional internal team, brought in the hospital procurement and supply managers BD had relationships with, and then reached out to hospitals' infection-prevention and occupational health leaders. Eventually product designers, nurses, sustainability staffers, and even hospital CFOs were using the platform, contributing data that generated new best practices and reduced infections. PMID:23593769
Problem Solving in the General Mathematics Classroom
ERIC Educational Resources Information Center
Troutman, Andria Price; Lichtenberg, Betty Plunkett
1974-01-01
Five steps common to different problem solving models are listed. Next, seven specific abilities related to solving problems are discussed and examples given. Sample activities, appropriate to help in developing these specific abilities, are suggested. (LS)
Using Logo to Develop Problem Solving Skills.
ERIC Educational Resources Information Center
Denenberg, Stewart A.
1993-01-01
Proposes using computer programing teaching problem solving. Describes the problem-solving technique of Top-Down Design, discusses its application to LOGO, and provides examples of programs using LOGO. (MDH)
Perspectives on Problem Solving and Instruction
ERIC Educational Resources Information Center
van Merrienboer, Jeroen J. G.
2013-01-01
Most educators claim that problem solving is important, but they take very different perspective on it and there is little agreement on how it should be taught. This article aims to sort out the different perspectives and discusses problem solving as a goal, a method, and a skill. As a goal, problem solving should not be limited to well-structured…
Developing Creativity through Collaborative Problem Solving
ERIC Educational Resources Information Center
Albert, Lillie R.; Kim, Rina
2013-01-01
This paper discusses an alternative approach for developing problem solving experiences for students. The major argument is that students can develop their creativity by engaging in collaborative problem solving activities in which they apply a variety of mathematical methods creatively to solve problems. The argument is supported by: considering…
Kindergarten Students Solving Mathematical Word Problems
ERIC Educational Resources Information Center
Johnson, Nickey Owen
2013-01-01
The purpose of this study was to explore problem solving with kindergarten students. This line of inquiry is highly significant given that Common Core State Standards emphasize deep, conceptual understanding in mathematics as well as problem solving in kindergarten. However, there is little research on problem solving with kindergarten students.…
Collis-Romberg Mathematical Problem Solving Profiles.
ERIC Educational Resources Information Center
Collis, K. F.; Romberg, T. A.
Problem solving has become a focus of mathematics programs in Australia in recent years, necessitating the assessment of students' problem-solving abilities. This manual provides a problem-solving assessment and teaching resource package containing four elements: (1) profiles assessment items; (2) profiles diagnostic forms for recording individual…
Affect and Problem Solving: Two Theoretical Perspectives.
ERIC Educational Resources Information Center
McLeod, Douglas B.
Cognitive factors related to problem solving have been explored, but affective factors also play an important role in the teaching of mathematical problem solving. This paper outlines the theories of George Mandler and Bernard Weiner, providing a useful background for research related to affect and problem solving. Data related to the two theories…
LEGO Robotics: An Authentic Problem Solving Tool?
ERIC Educational Resources Information Center
Castledine, Alanah-Rei; Chalmers, Chris
2011-01-01
With the current curriculum focus on correlating classroom problem solving lessons to real-world contexts, are LEGO robotics an effective problem solving tool? This present study was designed to investigate this question and to ascertain what problem solving strategies primary students engaged with when working with LEGO robotics and whether the…
Fibonacci's Triangle: A Vehicle for Problem Solving.
ERIC Educational Resources Information Center
Ouellette, Hugh
1979-01-01
A method for solving certain types of problems is illustrated by problems related to Fibonacci's triangle. The method involves pattern recognition, generalizing, algebraic manipulation, and mathematical induction. (MP)
Solving optimization problems on computational grids.
Wright, S. J.; Mathematics and Computer Science
2001-05-01
Multiprocessor computing platforms, which have become more and more widely available since the mid-1980s, are now heavily used by organizations that need to solve very demanding computational problems. Parallel computing is now central to the culture of many research communities. Novel parallel approaches were developed for global optimization, network optimization, and direct-search methods for nonlinear optimization. Activity was particularly widespread in parallel branch-and-bound approaches for various problems in combinatorial and network optimization. As the cost of personal computers and low-end workstations has continued to fall, while the speed and capacity of processors and networks have increased dramatically, 'cluster' platforms have become popular in many settings. A somewhat different type of parallel computing platform know as a computational grid (alternatively, metacomputer) has arisen in comparatively recent times. Broadly speaking, this term refers not to a multiprocessor with identical processing nodes but rather to a heterogeneous collection of devices that are widely distributed, possibly around the globe. The advantage of such platforms is obvious: they have the potential to deliver enormous computing power. Just as obviously, however, the complexity of grids makes them very difficult to use. The Condor team, headed by Miron Livny at the University of Wisconsin, were among the pioneers in providing infrastructure for grid computations. More recently, the Globus project has developed technologies to support computations on geographically distributed platforms consisting of high-end computers, storage and visualization devices, and other scientific instruments. In 1997, we started the metaneos project as a collaborative effort between optimization specialists and the Condor and Globus groups. Our aim was to address complex, difficult optimization problems in several areas, designing and implementing the algorithms and the software
ERIC Educational Resources Information Center
Bilgin, Ibrahim
2006-01-01
The purpose of this study was to investigate the effects of pair problem solving technique incorporating Polya's problem solving strategy on undergraduate students' performance in conceptual and algorithmic questions in chemistry. The subjects of this study were 89 students enrolled from two first year chemistry classes. The experimental group was…
Assessing Cognitive Learning of Analytical Problem Solving
NASA Astrophysics Data System (ADS)
Billionniere, Elodie V.
Introductory programming courses, also known as CS1, have a specific set of expected outcomes related to the learning of the most basic and essential computational concepts in computer science (CS). However, two of the most often heard complaints in such courses are that (1) they are divorced from the reality of application and (2) they make the learning of the basic concepts tedious. The concepts introduced in CS1 courses are highly abstract and not easily comprehensible. In general, the difficulty is intrinsic to the field of computing, often described as "too mathematical or too abstract." This dissertation presents a small-scale mixed method study conducted during the fall 2009 semester of CS1 courses at Arizona State University. This study explored and assessed students' comprehension of three core computational concepts---abstraction, arrays of objects, and inheritance---in both algorithm design and problem solving. Through this investigation students' profiles were categorized based on their scores and based on their mistakes categorized into instances of five computational thinking concepts: abstraction, algorithm, scalability, linguistics, and reasoning. It was shown that even though the notion of computational thinking is not explicit in the curriculum, participants possessed and/or developed this skill through the learning and application of the CS1 core concepts. Furthermore, problem-solving experiences had a direct impact on participants' knowledge skills, explanation skills, and confidence. Implications for teaching CS1 and for future research are also considered.
Teaching Top-Down Problem Solving.
ERIC Educational Resources Information Center
Patrick, Charles
Top-down problem solving is a methodical approach to obtaining real solutions for open-ended problems common in the realms of engineering and science. The technique provides a means for logically understanding a problem prior to attempting a solution. Steps in the top-down problem-solving method include the following: (1) identifying a need; (2)…
Super 7: Daily Exercises in Problem Solving.
ERIC Educational Resources Information Center
Hamilton, Octavia
This book is a year-long program of daily exercises in problem solving for 2nd and 3rd grade students that presents 144 lessons, each with seven problems. The problems cover number sense, computation, measurements, geometry, problem solving, and patterns. The material is presented in a sequential fashion with concepts repeated and expanded, and…
Algorithmic Perspectives on Problem Formulations in MDO
NASA Technical Reports Server (NTRS)
Alexandrov, Natalia M.; Lewis, Robert Michael
2000-01-01
This work is concerned with an approach to formulating the multidisciplinary optimization (MDO) problem that reflects an algorithmic perspective on MDO problem solution. The algorithmic perspective focuses on formulating the problem in light of the abilities and inabilities of optimization algorithms, so that the resulting nonlinear programming problem can be solved reliably and efficiently by conventional optimization techniques. We propose a modular approach to formulating MDO problems that takes advantage of the problem structure, maximizes the autonomy of implementation, and allows for multiple easily interchangeable problem statements to be used depending on the available resources and the characteristics of the application problem.
Analog Processor To Solve Optimization Problems
NASA Technical Reports Server (NTRS)
Duong, Tuan A.; Eberhardt, Silvio P.; Thakoor, Anil P.
1993-01-01
Proposed analog processor solves "traveling-salesman" problem, considered paradigm of global-optimization problems involving routing or allocation of resources. Includes electronic neural network and auxiliary circuitry based partly on concepts described in "Neural-Network Processor Would Allocate Resources" (NPO-17781) and "Neural Network Solves 'Traveling-Salesman' Problem" (NPO-17807). Processor based on highly parallel computing solves problem in significantly less time.
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)
Problem-Solving Test: Pyrosequencing
ERIC Educational Resources Information Center
Szeberenyi, Jozsef
2013-01-01
Terms to be familiar with before you start to solve the test: Maxam-Gilbert sequencing, Sanger sequencing, gel electrophoresis, DNA synthesis reaction, polymerase chain reaction, template, primer, DNA polymerase, deoxyribonucleoside triphosphates, orthophosphate, pyrophosphate, nucleoside monophosphates, luminescence, acid anhydride bond,…
Error Detection Processes in Problem Solving.
ERIC Educational Resources Information Center
Allwood, Carl Martin
1984-01-01
Describes a study which analyzed problem solvers' error detection processes by instructing subjects to think aloud when solving statistical problems. Effects of evaluative episodes on error detection, detection of different error types, error detection processes per se, and relationship of error detection behavior to problem-solving proficiency…
Distributed problem solving by pilots and dispatchers
NASA Technical Reports Server (NTRS)
Orasanu, Judith; Wich, Mike; Fischer, Ute; Jobe, Kim; Mccoy, Elaine; Beatty, Roger; Smith, Phil
1993-01-01
The study addressed the following question: Are flight planning problems solved differently by PILOTS and DISPATCHERS when they work alone versus when they work together? Aspect of their performance that were of interest include the following: Problem perception and definition; Problem solving strategies and information use; Options considered; Solution and rational; and errors.
General Description of Human Problem Solving.
ERIC Educational Resources Information Center
Klein, Gary A.; Weitzenfeld, Julian
A theoretical model relating problem identification to problem solving is presented. The main purpose of the study is to increase understanding of decision making among Air Force educators. The problem-solving process is defined as the generation and evaluation of alternatives that will accomplish what is needed and the reidentification of what is…
Applications of Symmetry to Problem Solving.
ERIC Educational Resources Information Center
Leikin, Roza; Berman, Abraham; Zaslavsky, Orit
2000-01-01
Symmetry is an important mathematical concept that plays an extremely important role as a problem solving technique. Presents examples of problems from several branches of mathematics that can be solved using different types of symmetry. Discusses teachers' attitudes and beliefs regarding the use of symmetry in the solutions of these problems.…
Problem solving in health services organizations.
Rakich, J S; Krigline, A B
1996-01-01
Health services organization managers at all levels are constantly confronted with problems. Conditions encountered that initiate the need for problem solving are opportunity, threat, crisis, deviation, and improvement. A general problem-solving model presenting an orderly process by which managers can approach this important task is described. An example of the model applied to the current strategic climate is presented. PMID:10158720
Mobile serious games for collaborative problem solving.
Sanchez, Jaime; Mendoza, Claudia; Salinas, Alvaro
2009-01-01
This paper presents the results obtained from the implementation of a series of learning activities based on mobile serious games (MSG) for the development of problem-solving and collaborative skills in Chilean 8th grade students. Three MSGs were developed and played by teams of four students, who had to solve the problems posed by the game collaboratively. The data shows that the experimental group had a higher perception of their own skills of collaboration and of the plan execution dimension of problem solving than the control group, providing empirical evidence regarding the contribution of MSGs to the development of collaborative problem-solving skills. PMID:19592762
Secondary School Genetics Instruction: Making Problem Solving Explicit and Meaningful.
ERIC Educational Resources Information Center
Thomson, Norman; Stewart, James
1985-01-01
Explains an algorithm which details procedures for solving a broad class of genetics problems common to pre-college biology. Several flow charts (developed from the algorithm) are given with sample questions and suggestions for student use. Conclusions are based on the authors' research (which includes student interviews and textbook analyses).…
Disciplinary Foundations for Solving Interdisciplinary Scientific Problems
NASA Astrophysics Data System (ADS)
Zhang, Dongmei; Shen, Ji
2015-10-01
Problem-solving has been one of the major strands in science education research. But much of the problem-solving research has been conducted on discipline-based contexts; little research has been done on how students, especially individuals, solve interdisciplinary problems. To understand how individuals reason about interdisciplinary problems, we conducted an interview study with 16 graduate students coming from a variety of disciplinary backgrounds. During the interviews, we asked participants to solve two interdisciplinary science problems on the topic of osmosis. We investigated participants' problem reasoning processes and probed in their attitudes toward general interdisciplinary approach and specific interdisciplinary problems. Through a careful inductive content analysis of their responses, we studied how disciplinary, cognitive, and affective factors influenced their interdisciplinary problems-solving. We found that participants' prior discipline-based science learning experiences had both positive and negative influences on their interdisciplinary problem-solving. These influences were embodied in their conceptualization of the interdisciplinary problems, the strategies they used to integrate different disciplinary knowledge, and the attitudes they had toward interdisciplinary approach in general and specific interdisciplinary problems. This study sheds light on interdisciplinary science education by revealing the complex relationship between disciplinary learning and interdisciplinary problem-solving.
Pen Pals: Practicing Problem Solving
ERIC Educational Resources Information Center
Lampe, Kristen A.; Uselmann, Linda
2008-01-01
This article describes a semester-long pen-pal project in which preservice teachers composed mathematical problems and the middle school students worked for solutions. The college students assessed the solution and the middle school students provided feedback regarding the problem itself. (Contains 6 figures.)
Readiness for Solving Story Problems.
ERIC Educational Resources Information Center
Dunlap, William F.
1982-01-01
Readiness activities are described which are designed to help learning disabled (LD) students learn to perform computations in story problems. Activities proceed from concrete objects to numbers and involve the students in devising story problems. The language experience approach is incorporated with the enactive, iconic, and symbolic levels of…
NASA Astrophysics Data System (ADS)
Easton, Don
1999-03-01
This note is a description of a student solution to a problem. I found the solution exciting because it exemplifies the kind of solution by analogy that Feynman describes in The Feynman Lectures on Physics.
Problem Solving, Patterns, Probability, Pascal, and Palindromes.
ERIC Educational Resources Information Center
Hylton-Lindsay, Althea Antoinette
2003-01-01
Presents a problem-solving activity, the birth order problem, and several solution-seeking strategies. Includes responses of current and prospective teachers and a comparison of various strategies. (YDS)
Neural Network Solves "Traveling-Salesman" Problem
NASA Technical Reports Server (NTRS)
Thakoor, Anilkumar P.; Moopenn, Alexander W.
1990-01-01
Experimental electronic neural network solves "traveling-salesman" problem. Plans round trip of minimum distance among N cities, visiting every city once and only once (without backtracking). This problem is paradigm of many problems of global optimization (e.g., routing or allocation of resources) occuring in industry, business, and government. Applied to large number of cities (or resources), circuits of this kind expected to solve problem faster and more cheaply.
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.
Solving the Tulsa ozone problem
Wagner, K.K.; Wilson, J.D.; Gibeau, E.
1998-12-31
Local governments and interested parties in Tulsa, Oklahoma are planning actions to keep Tulsa in compliance with the ozone ambient air quality standard. Based on recent data Tulsa exceeds the new eight hour average national ambient air quality standard for ozone and occasionally exceeds the previous one hour standard. Currently, Tulsa is in attainment of the former one-hour ozone standard. The first planning step is to integrate the existing information about Tulsa`s ozone problem. Prior studies of Tulsa ozone are reviewed. Tulsa`s recent air quality and meteorological monitoring are evaluated. Emission inventory estimates are assessed. Factors identified with Tulsa`s ozone problem are the transport of ozone and precursor gases, a possible role for biogenic emissions, and a simplistic ozone forecasting method. The integration of information found that current air quality and meteorological monitoring is meager. Observations of volatile organic compounds and NO{sub y} are absent. Prior intensive studies in 1977 and 1985 are more than ten years old and lack relevance to today`s problem. Emission inventory estimates are scarce and uncertain. The current knowledge base was judged inadequate to properly characterize the present ozone problem. Actions are recommended to enlarge the information base to address Tulsa`s ozone problem.
Taking "From Scratch" out of Problem Solving
ERIC Educational Resources Information Center
Brown, Wayne
2007-01-01
Solving problems and creating processes and procedures from the ground up has long been part of the IT department's way of operating. IT staffs will continue to encounter new problems to solve and new technologies to be implemented. They also must involve their constituents in the creation of solutions. Nonetheless, for many issues they no longer…
A Problem-Solving Model for Instruction.
ERIC Educational Resources Information Center
Scott, Roger O.
This second in a series of three papers on the Associated Staff Training Program of the Foreign Language Innovative Curriculum Study concentrates on the problem solving strategy employed by the program's specially trained innovative agents--the Instructional Systems Consultants (ISC). The problem-solving method used is first illustrated by citing…
Conceptual Problem Solving in High School Physics
ERIC Educational Resources Information Center
Docktor, Jennifer L.; Strand, Natalie E.; Mestre, José P.; Ross, Brian H.
2015-01-01
Problem solving is a critical element of learning physics. However, traditional instruction often emphasizes the quantitative aspects of problem solving such as equations and mathematical procedures rather than qualitative analysis for selecting appropriate concepts and principles. This study describes the development and evaluation of an…
Solving Problems in Genetics II: Conceptual Restructuring
ERIC Educational Resources Information Center
Orcajo, Teresa Ibanez; Aznar, Mercedes Martinez
2005-01-01
This paper presents the results of part of an investigation carried out with fourth-level Spanish secondary education students (15 years old), in which we implemented a teaching unit based on problem-solving methodology as an investigation to teach genetics and human inheritance curricular contents. By solving open problems, the students…
Problem Solving Software for Math Classes.
ERIC Educational Resources Information Center
Troutner, Joanne
1987-01-01
Described are 10 computer software programs for problem solving related to mathematics. Programs described are: (1) Box Solves Story Problems; (2) Safari Search; (3) Puzzle Tanks; (4) The King's Rule; (5) The Factory; (6) The Royal Rules; (7) The Enchanted Forest; (8) Gears; (9) The Super Factory; and (10) Creativity Unlimited. (RH)
Solving Problems with Charts & Tables. Pipefitter.
ERIC Educational Resources Information Center
Greater Baton Rouge Chamber of Commerce, LA.
Developed as part of the ABCs of Construction National Workplace Literacy Project, this instructional module is designed to help individuals employed as pipefitters learn to solve problems with charts and tables. Outlined in the first section is a five-step procedure for solving problems involving tables and/or charts: identifying the question to…
Student Modeling Based on Problem Solving Times
ERIC Educational Resources Information Center
Pelánek, Radek; Jarušek, Petr
2015-01-01
Student modeling in intelligent tutoring systems is mostly concerned with modeling correctness of students' answers. As interactive problem solving activities become increasingly common in educational systems, it is useful to focus also on timing information associated with problem solving. We argue that the focus on timing is natural for certain…
Metacognition: Student Reflections on Problem Solving
ERIC Educational Resources Information Center
Wismath, Shelly; Orr, Doug; Good, Brandon
2014-01-01
Twenty-first century teaching and learning focus on the fundamental skills of critical thinking and problem solving, creativity and innovation, and collaboration and communication. Metacognition is a crucial aspect of both problem solving and critical thinking, but it is often difficult to get students to engage in authentic metacognitive…
Mathematical Problem Solving through Sequential Process Analysis
ERIC Educational Resources Information Center
Codina, A.; Cañadas, M. C.; Castro, E.
2015-01-01
Introduction: The macroscopic perspective is one of the frameworks for research on problem solving in mathematics education. Coming from this perspective, our study addresses the stages of thought in mathematical problem solving, offering an innovative approach because we apply sequential relations and global interrelations between the different…
Problem Solving and Technology. ACESIA Monograph 2.
ERIC Educational Resources Information Center
Lomon, Earle L.; And Others
1977-01-01
The two articles dealing with problem solving and technology in this publication should be useful to those developing the kinds of materials, experiences, and thinking that elementary school industrial arts offers children. The first article accepts problem solving as an educational goal and reports a timely and universally acceptable approach.…
Geographic Information Systems: Implications for Problem Solving.
ERIC Educational Resources Information Center
Audet, Richard H.; Abegg, Gerald L.
1996-01-01
Compares expert-/novice-based problem-solving behaviors with a Geographic Information Systems program. Uses naturalistic methods to analyze problem-solving strategies for occurrence of thematic elements. Reports that experts relied on logical formulations to query the database while novices used trial-and-error methods and midlevel cognitive…
Children Solving Problems. The Developing Child Series.
ERIC Educational Resources Information Center
Thornton, Stephanie
The developmental increase in the ability to solve problems is a puzzle. Does it come from basic changes in mental skills, or is it a matter of practice? This book from the Developing Child series synthesizes recent research examining children's problem-solving skills development. Chapter 1 presents the major themes: (1) there is increasing…
Dynamic Problem Solving: A New Assessment Perspective
ERIC Educational Resources Information Center
Greiff, Samuel; Wustenberg, Sascha; Funke, Joachim
2012-01-01
This article addresses two unsolved measurement issues in dynamic problem solving (DPS) research: (a) unsystematic construction of DPS tests making a comparison of results obtained in different studies difficult and (b) use of time-intensive single tasks leading to severe reliability problems. To solve these issues, the MicroDYN approach is…
Could HPS Improve Problem-Solving?
ERIC Educational Resources Information Center
Coelho, Ricardo Lopes
2013-01-01
It is generally accepted nowadays that History and Philosophy of Science (HPS) is useful in understanding scientific concepts, theories and even some experiments. Problem-solving strategies are a significant topic, since students' careers depend on their skill to solve problems. These are the reasons for addressing the question of whether problem…
Problem Solving Interactions on Electronic Networks.
ERIC Educational Resources Information Center
Waugh, Michael; And Others
Arguing that electronic networking provides a medium which is qualitatively superior to the traditional classroom for conducting certain types of problem solving exercises, this paper details the Water Problem Solving Project, which was conducted on the InterCultural Learning Network in 1985 and 1986 with students from the United States, Mexico,…
Teaching and Learning through Problem Solving
ERIC Educational Resources Information Center
Ollerton, Mike
2007-01-01
In this article, the author relates some problem solving work with primary schools to Department for Children, Schools, and Families (DfES) support. In four primary schools in the West Midlands, the focus was teaching mathematics through problem solving, based on materials published on the DfES "standards" website. The author noticed the way…
Measuring Problem Solving Skills in "Portal 2"
ERIC Educational Resources Information Center
Shute, Valerie J.; Wang, Lubin
2013-01-01
This paper examines possible improvement to problem solving skills as a function of playing the video game "Portal 2." Stealth assessment is used in the game to evaluate students' problem solving abilities--specifically basic and flexible rule application. The stealth assessment measures will be validated against commonly accepted…
A Multivariate Model of Physics Problem Solving
ERIC Educational Resources Information Center
Taasoobshirazi, Gita; Farley, John
2013-01-01
A model of expertise in physics problem solving was tested on undergraduate science, physics, and engineering majors enrolled in an introductory-level physics course. Structural equation modeling was used to test hypothesized relationships among variables linked to expertise in physics problem solving including motivation, metacognitive planning,…
Problem Solving Software: What Does It Teach?
ERIC Educational Resources Information Center
Duffield, Judith A.
The purpose of this study was to examine the potential of computer-assisted instruction (CAI) for teaching problem solving skills. It was conducted in three phases. During the first phase, two pieces of problem solving software, "The King's Rule" and "Safari Search," were identified and analyzed. During the second phase, two groups of six…
Developing Legal Problem-Solving Skills.
ERIC Educational Resources Information Center
Nathanson, Stephen
1994-01-01
A law professor explains how he came to view legal problem solving as the driving concept in law school curriculum design and draws on personal experience and a survey of students concerning teaching methods in a commercial law course. He outlines six curriculum design principles for teaching legal problem solving. (MSE)
Beyond Computation: Improving Mathematical Problem Solving.
ERIC Educational Resources Information Center
Anderson, Jennifer M.; Olson, Jennifer S.; Wrobel, Margaret L.
This action research describes a program for improving mathematical problem solving skills. The targeted population consisted of first grade students in a transient, middle class community as well as third and sixth grade students from a growing, middle to upper class in Illinois. The concerns of problem solving were documented through teacher…
ERIC Educational Resources Information Center
Aljaberi, Nahil M.; Gheith, Eman
2016-01-01
This study aims to investigate the ability of pre-service class teacher at University of Petrain solving mathematical problems using Polya's Techniques, their level of problem solving skills in daily-life issues. The study also investigates the correlation between their ability to solve mathematical problems and their level of problem solving…
Solving search problems by strongly simulating quantum circuits
Johnson, T. H.; Biamonte, J. D.; Clark, S. R.; Jaksch, D.
2013-01-01
Simulating quantum circuits using classical computers lets us analyse the inner workings of quantum algorithms. The most complete type of simulation, strong simulation, is believed to be generally inefficient. Nevertheless, several efficient strong simulation techniques are known for restricted families of quantum circuits and we develop an additional technique in this article. Further, we show that strong simulation algorithms perform another fundamental task: solving search problems. Efficient strong simulation techniques allow solutions to a class of search problems to be counted and found efficiently. This enhances the utility of strong simulation methods, known or yet to be discovered, and extends the class of search problems known to be efficiently simulable. Relating strong simulation to search problems also bounds the computational power of efficiently strongly simulable circuits; if they could solve all problems in P this would imply that all problems in NP and #P could be solved in polynomial time. PMID:23390585
Solving the wrong hierarchy problem
NASA Astrophysics Data System (ADS)
Blinov, Nikita; Hook, Anson
2016-06-01
Many theories require augmenting the Standard Model with additional scalar fields with large order one couplings. We present a new solution to the hierarchy problem for these scalar fields. We explore parity- and Z_2 -symmetric theories where the Standard Model Higgs potential has two vacua. The parity or Z_2 copy of the Higgs lives in the minimum far from the origin while our Higgs occupies the minimum near the origin of the potential. This approach results in a theory with multiple light scalar fields but with only a single hierarchy problem, since the bare mass is tied to the Higgs mass by a discrete symmetry. The new scalar does not have a new hierarchy problem associated with it because its expectation value and mass are generated by dimensional transmutation of the scalar quartic coupling. The location of the second Higgs minimum is not a free parameter, but is rather a function of the matter content of the theory. As a result, these theories are extremely predictive. We develop this idea in the context of a solution to the strong CP problem. We show this mechanism postdicts the top Yukawa to be within 1 σ of the currently measured value and predicts scalar color octets with masses in the range 9-200 TeV.
Solving a Spacecraft Design Problem
NASA Technical Reports Server (NTRS)
Fisher, D. K.
1998-01-01
We have probably all been amazed at the ingenuity of spacecraft engineers when we see some of the solutions they invent for such problems as landing a roving vehicle on Mars-as engineers at the Jet Propulsion Laboratory did for NASA's Mars Pathfinder project-without using retro-rockets or even putting a spacecraft in orbit first.
Robot, computer problem solving system
NASA Technical Reports Server (NTRS)
Becker, J. D.; Merriam, E. W.
1973-01-01
The TENEX computer system, the ARPA network, and computer language design technology was applied to support the complex system programs. By combining the pragmatic and theoretical aspects of robot development, an approach is created which is grounded in realism, but which also has at its disposal the power that comes from looking at complex problems from an abstract analytical point of view.
Solving the wrong hierarchy problem
Blinov, Nikita; Hook, Anson
2016-06-29
Many theories require augmenting the Standard Model with additional scalar fields with large order one couplings. We present a new solution to the hierarchy problem for these scalar fields. We explore parity- and Z2-symmetric theories where the Standard Model Higgs potential has two vacua. The parity or Z2 copy of the Higgs lives in the minimum far from the origin while our Higgs occupies the minimum near the origin of the potential. This approach results in a theory with multiple light scalar fields but with only a single hierarchy problem, since the bare mass is tied to the Higgs massmore » by a discrete symmetry. The new scalar does not have a new hierarchy problem associated with it because its expectation value and mass are generated by dimensional transmutation of the scalar quartic coupling. The location of the second Higgs minimum is not a free parameter, but is rather a function of the matter content of the theory. As a result, these theories are extremely predictive. We develop this idea in the context of a solution to the strong CP problem. Lastly, we show this mechanism postdicts the top Yukawa to be within 1σ of the currently measured value and predicts scalar color octets with masses in the range 9-200 TeV.« less
Sour landfill gas problem solved
Nagl, G.; Cantrall, R.
1996-05-01
In Broward County, Fla., near Pompano Beach, Waste Management of North America (WMNA, a subsidiary of WMX Technologies, Oak Brook, IL) operates the Central Sanitary Landfill and Recycling Center, which includes the country`s largest landfill gas-to-energy plant. The landfill consists of three collection sites: one site is closed, one is currently receiving garbage, and one will open in the future. Approximately 9 million standard cubic feet (scf) per day of landfill gas is collected from approximately 300 wells spread over the 250-acre landfill. With a dramatic increase of sulfur-containing waste coming to a South Florida landfill following Hurricane Andrew, odors related to hydrogen sulfide became a serious problem. However, in a matter of weeks, an innovative desulfurization unit helped calm the landfill operator`s fears. These very high H{sub 2}S concentrations caused severe odor problems in the surrounding residential area, corrosion problems in the compressors, and sulfur dioxide (SO{sub 2}) emission problems in the exhaust gas from the turbine generators.
Energy Landscapes and Solved Protein Folding Problems
NASA Astrophysics Data System (ADS)
Wolynes, Peter
2004-03-01
Peter G. Wolynes Center for Theoretical Biological Physics Department of Chemistry and Biochemistry and Physics University of California, San Diego La Jolla, CA 92093-0371 Fifteen years ago, how proteins folded into organized structures on the basis of their sequence was a great mystery. By characterizing the energy landscapes of proteins with tools from the statistical mechanics of disordered systems like spin glasses, a "new view' of the folding process became possible. Energy landscape theory provided an incentive to pursue heroic new experiments and to carry out difficult computer simulations addressing protein folding mechanisms. Many aspects of folding kinetics revealed by these studies can be quantitatively understood using the simple idea that the topography of the energy landscape is that of a "rugged funnel". Energy landscape theory provided a quantitative means of characterizing which amino acid sequences can rapidly fold. Algorithms based on energy landscape theory have been used to successfully design novel sequences that fold to a given structure in the laboratory. Energy landscape ideas have begun to transform the prediction of protein structure from sequence data from being an art to being a science. The success of energy landscape- based algorithms in predicting protein structure from sequence will be highlighted. While there is still much to learn about folding mechanisms and much work to do achieving universally reliable structure prediction, many parts of what used to be called "the protein folding problem" can now be considered solved.
Efficient algorithms for proximity problems
Wee, Y.C.
1989-01-01
Computational geometry is currently a very active area of research in computer science because of its applications to VLSI design, database retrieval, robotics, pattern recognition, etc. The author studies a number of proximity problems which are fundamental in computational geometry. Optimal or improved sequential and parallel algorithms for these problems are presented. Along the way, some relations among the proximity problems are also established. Chapter 2 presents an O(N log{sup 2} N) time divide-and-conquer algorithm for solving the all pairs geographic nearest neighbors problem (GNN) for a set of N sites in the plane under any L{sub p} metric. Chapter 3 presents an O(N log N) divide-and-conquer algorithm for computing the angle restricted Voronoi diagram for a set of N sites in the plane. Chapter 4 introduces a new data structure for the dynamic version of GNN. Chapter 5 defines a new formalism called the quasi-valid range aggregation. This formalism leads to a new and simple method for reducing non-range query-like problems to range queries and often to orthogonal range queries, with immediate applications to the attracted neighbor and the planar all-pairs nearest neighbors problem. Chapter 6 introduces a new approach for the construction of the Voronoi diagram. Using this approach, we design an O(log N) time O (N) processor algorithm for constructing the Voronoi diagram with L{sub 1} and L. metrics on a CREW PRAM machine. Even though the GNN and the Delaunay triangulation (DT) do not have an inclusion relation, we show, using some range type queries, how to efficiently construct DT from the GNN relations over a constant number of angular ranges.
NASA Astrophysics Data System (ADS)
Pei, Jun; Liu, Xinbao; Pardalos, Panos M.; Fan, Wenjuan; Wang, Ling; Yang, Shanlin
2016-03-01
Motivated by applications in manufacturing industry, we consider a supply chain scheduling problem, where each job is characterised by non-identical sizes, different release times and unequal processing times. The objective is to minimise the makespan by making batching and sequencing decisions. The problem is formalised as a mixed integer programming model and proved to be strongly NP-hard. Some structural properties are presented for both the general case and a special case. Based on these properties, a lower bound is derived, and a novel two-phase heuristic (TP-H) is developed to solve the problem, which guarantees to obtain a worst case performance ratio of ?. Computational experiments with a set of different sizes of random instances are conducted to evaluate the proposed approach TP-H, which is superior to another two heuristics proposed in the literature. Furthermore, the experimental results indicate that TP-H can effectively and efficiently solve large-size problems in a reasonable time.
Assertiveness and problem solving in midwives
Yurtsal, Zeliha Burcu; Özdemir, Levent
2015-01-01
Background: Midwifery profession is required to bring solutions to problems and a midwife is expected to be an assertive person and to develop midwifery care. This study was planned to examine the relationship between assertiveness and problem-solving skills of midwives. Materials and Methods: This cross-sectional study was conducted with 201 midwives between July 2008 and February 2009 in the city center of Sivas. The Rathus Assertiveness Schedule (RAS) and Problem Solving Inventory (PSI) were used to determine the level of assertiveness and problem-solving skills of midwives. Statistical methods were used as mean, standard deviation, percentage, Student's T, ANOVA and Tukey HSD, Kruskal Wallis, Fisher Exact, Pearson Correlation and Chi-square tests and P < 0.05. Results: The RAS mean scores and the PSI mean scores showed statistically significant differences in terms of a midwife's considering herself as a member of the health team, expressing herself within the health care team, being able to say “no” when necessary, cooperating with her colleagues, taking part in problem-solving skills training. A statistically significant negative correlation was found between the RAS and PSI scores. The RAS scores decreased while the problem-solving scores increased (r: -0451, P < 0.01). Conclusions: There were significant statistical differences between assertiveness levels and problem solving skills of midwives, and midwives who were assertive solved their problems better than did others. Assertiveness and problem-solving skills training will contribute to the success of the midwifery profession. Midwives able to solve problems, and display assertive behaviors will contribute to the development of midwifery profession. PMID:26793247
Cognitive Problems (Disorientation, Perception, Attention, Learning and Problem-Solving)
... SOMEONE WITH EMOTIONAL & BEHAVIORAL NEEDS Cognitive Problems (Disorientation, Perception, Attention, Learning & Problem-Solving) Cognition is the process ... What Are Some Other Cognitive Problems? What Is Perception? Remember What Is Attention or Concentration? More Resources ...
Lesion mapping of social problem solving
Colom, Roberto; Paul, Erick J.; Chau, Aileen; Solomon, Jeffrey; Grafman, Jordan H.
2014-01-01
Accumulating neuroscience evidence indicates that human intelligence is supported by a distributed network of frontal and parietal regions that enable complex, goal-directed behaviour. However, the contributions of this network to social aspects of intellectual function remain to be well characterized. Here, we report a human lesion study (n = 144) that investigates the neural bases of social problem solving (measured by the Everyday Problem Solving Inventory) and examine the degree to which individual differences in performance are predicted by a broad spectrum of psychological variables, including psychometric intelligence (measured by the Wechsler Adult Intelligence Scale), emotional intelligence (measured by the Mayer, Salovey, Caruso Emotional Intelligence Test), and personality traits (measured by the Neuroticism-Extraversion-Openness Personality Inventory). Scores for each variable were obtained, followed by voxel-based lesion–symptom mapping. Stepwise regression analyses revealed that working memory, processing speed, and emotional intelligence predict individual differences in everyday problem solving. A targeted analysis of specific everyday problem solving domains (involving friends, home management, consumerism, work, information management, and family) revealed psychological variables that selectively contribute to each. Lesion mapping results indicated that social problem solving, psychometric intelligence, and emotional intelligence are supported by a shared network of frontal, temporal, and parietal regions, including white matter association tracts that bind these areas into a coordinated system. The results support an integrative framework for understanding social intelligence and make specific recommendations for the application of the Everyday Problem Solving Inventory to the study of social problem solving in health and disease. PMID:25070511
Lesion mapping of social problem solving.
Barbey, Aron K; Colom, Roberto; Paul, Erick J; Chau, Aileen; Solomon, Jeffrey; Grafman, Jordan H
2014-10-01
Accumulating neuroscience evidence indicates that human intelligence is supported by a distributed network of frontal and parietal regions that enable complex, goal-directed behaviour. However, the contributions of this network to social aspects of intellectual function remain to be well characterized. Here, we report a human lesion study (n = 144) that investigates the neural bases of social problem solving (measured by the Everyday Problem Solving Inventory) and examine the degree to which individual differences in performance are predicted by a broad spectrum of psychological variables, including psychometric intelligence (measured by the Wechsler Adult Intelligence Scale), emotional intelligence (measured by the Mayer, Salovey, Caruso Emotional Intelligence Test), and personality traits (measured by the Neuroticism-Extraversion-Openness Personality Inventory). Scores for each variable were obtained, followed by voxel-based lesion-symptom mapping. Stepwise regression analyses revealed that working memory, processing speed, and emotional intelligence predict individual differences in everyday problem solving. A targeted analysis of specific everyday problem solving domains (involving friends, home management, consumerism, work, information management, and family) revealed psychological variables that selectively contribute to each. Lesion mapping results indicated that social problem solving, psychometric intelligence, and emotional intelligence are supported by a shared network of frontal, temporal, and parietal regions, including white matter association tracts that bind these areas into a coordinated system. The results support an integrative framework for understanding social intelligence and make specific recommendations for the application of the Everyday Problem Solving Inventory to the study of social problem solving in health and disease. PMID:25070511
The Cyclic Nature of Problem Solving: An Emergent Multidimensional Problem-Solving Framework
ERIC Educational Resources Information Center
Carlson, Marilyn P.; Bloom, Irene
2005-01-01
This paper describes the problem-solving behaviors of 12 mathematicians as they completed four mathematical tasks. The emergent problem-solving framework draws on the large body of research, as grounded by and modified in response to our close observations of these mathematicians. The resulting "Multidimensional Problem-Solving Framework" has four…
Spatial visualization in physics problem solving.
Kozhevnikov, Maria; Motes, Michael A; Hegarty, Mary
2007-07-01
Three studies were conducted to examine the relation of spatial visualization to solving kinematics problems that involved either predicting the two-dimensional motion of an object, translating from one frame of reference to another, or interpreting kinematics graphs. In Study 1, 60 physics-naíve students were administered kinematics problems and spatial visualization ability tests. In Study 2, 17 (8 high- and 9 low-spatial ability) additional students completed think-aloud protocols while they solved the kinematics problems. In Study 3, the eye movements of fifteen (9 high- and 6 low-spatial ability) students were recorded while the students solved kinematics problems. In contrast to high-spatial students, most low-spatial students did not combine two motion vectors, were unable to switch frames of reference, and tended to interpret graphs literally. The results of the study suggest an important relationship between spatial visualization ability and solving kinematics problems with multiple spatial parameters. PMID:21635308
Could HPS Improve Problem-Solving?
NASA Astrophysics Data System (ADS)
Coelho, Ricardo Lopes
2013-05-01
It is generally accepted nowadays that History and Philosophy of Science (HPS) is useful in understanding scientific concepts, theories and even some experiments. Problem-solving strategies are a significant topic, since students' careers depend on their skill to solve problems. These are the reasons for addressing the question of whether problem solving could be improved by means of HPS. Three typical problems in introductory courses of mechanics—the inclined plane, the simple pendulum and the Atwood machine—are taken as the object of the present study. The solving strategies of these problems in the eighteenth and nineteenth century constitute the historical component of the study. Its philosophical component stems from the foundations of mechanics research literature. The use of HPS leads us to see those problems in a different way. These different ways can be tested, for which experiments are proposed. The traditional solving strategies for the incline and pendulum problems are adequate for some situations but not in general. The recourse to apparent weights in the Atwood machine problem leads us to a new insight and a solving strategy for composed Atwood machines. Educational implications also concern the development of logical thinking by means of the variety of lines of thought provided by HPS.
Unsupervised neural networks for solving Troesch's problem
NASA Astrophysics Data System (ADS)
Muhammad, Asif Zahoor Raja
2014-01-01
In this study, stochastic computational intelligence techniques are presented for the solution of Troesch's boundary value problem. The proposed stochastic solvers use the competency of a feed-forward artificial neural network for mathematical modeling of the problem in an unsupervised manner, whereas the learning of unknown parameters is made with local and global optimization methods as well as their combinations. Genetic algorithm (GA) and pattern search (PS) techniques are used as the global search methods and the interior point method (IPM) is used for an efficient local search. The combination of techniques like GA hybridized with IPM (GA-IPM) and PS hybridized with IPM (PS-IPM) are also applied to solve different forms of the equation. A comparison of the proposed results obtained from GA, PS, IPM, PS-IPM and GA-IPM has been made with the standard solutions including well known analytic techniques of the Adomian decomposition method, the variational iterational method and the homotopy perturbation method. The reliability and effectiveness of the proposed schemes, in term of accuracy and convergence, are evaluated from the results of statistical analysis based on sufficiently large independent runs.
Solving inversion problems with neural networks
NASA Technical Reports Server (NTRS)
Kamgar-Parsi, Behzad; Gualtieri, J. A.
1990-01-01
A class of inverse problems in remote sensing can be characterized by Q = F(x), where F is a nonlinear and noninvertible (or hard to invert) operator, and the objective is to infer the unknowns, x, from the observed quantities, Q. Since the number of observations is usually greater than the number of unknowns, these problems are formulated as optimization problems, which can be solved by a variety of techniques. The feasibility of neural networks for solving such problems is presently investigated. As an example, the problem of finding the atmospheric ozone profile from measured ultraviolet radiances is studied.
Problem Solving through an Optimization Problem in Geometry
ERIC Educational Resources Information Center
Poon, Kin Keung; Wong, Hang-Chi
2011-01-01
This article adapts the problem-solving model developed by Polya to investigate and give an innovative approach to discuss and solve an optimization problem in geometry: the Regiomontanus Problem and its application to football. Various mathematical tools, such as calculus, inequality and the properties of circles, are used to explore and reflect…
Task Variables in Mathematical Problem Solving.
ERIC Educational Resources Information Center
Goldin, Gerald A., Ed.; McClintock, C. Edwin, Ed.
A framework for research in problem solving is provided by categorizing and defining variables describing problem tasks. A model is presented in an article by Kulm for the classification of task variables into broad categories. The model attempts to draw realtionships between these categories of task variables and the stages of problem solving…
Collaborative Problem Solving in Shared Space
ERIC Educational Resources Information Center
Lin, Lin; Mills, Leila A.; Ifenthaler, Dirk
2015-01-01
The purpose of this study was to examine collaborative problem solving in a shared virtual space. The main question asked was: How will the performance and processes differ between collaborative problem solvers and independent problem solvers over time? A total of 104 university students (63 female and 41 male) participated in an experimental…