Computing Tools for Modeling, Optimization and Simulation: Interfaces in Computer Science and Operations ResearchManuel Laguna, José Luis González-Velarde Computing Tools for Modeling, Optimization and Simulation reflects the need for preserving the marriage between operations research and computing in order to create more efficient and powerful software tools in the years ahead. The 17 papers included in this volume were carefully selected to cover a wide range of topics related to the interface between operations research and computer science. The volume includes the now perennial applications of rnetaheuristics (such as genetic algorithms, scatter search, and tabu search) as well as research on global optimization, knowledge management, software rnaintainability and object-oriented modeling. These topics reflect the complexity and variety of the problems that current and future software tools must be capable of tackling. The OR/CS interface is frequently at the core of successful applications and the development of new methodologies, making the research in this book a relevant reference in the future. The editors' goal for this book has been to increase the interest in the interface of computer science and operations research. Both researchers and practitioners will benefit from this book. The tutorial papers may spark the interest of practitioners for developing and applying new techniques to complex problems. In addition, the book includes papers that explore new angles of well-established methods for problems in the area of nonlinear optimization and mixed integer programming, which seasoned researchers in these fields may find fascinating. |
Contents
MultiStart and Strategic Oscillation Methods Principles to Exploit Adaptive Memory | 1 |
Building a Highquality Decision Tree with a Genetic Algorithm | 25 |
Sequential Testing of SeriesParallel Systems of Small Depth | 39 |
Conveying Problem Structure from an Algebraic Modeling Language to Optimization Algorithms | 75 |
Solving General Ring Network Design Problems by MetaHeuristics | 91 |
LagrangeanSurrogate Heuristics for pMedian Problems | 115 |
An Introduction to Ant Systems | 131 |
Extremal Energy Models and Global Optimization | 145 |
Knowledge Management and its Impact on Decision Support | 183 |
Heuristics for Minimum Cost SteadyState Gas Transmission Networks | 203 |
Assigning Proctors to Exams with Scatter Search | 215 |
MultiAttribute Evaluation of Software Maintainability | 229 |
ExplicitConstraint Branching for Solving Mixed Integer Programs | 245 |
An ObjectOriented Graphical Modeler for Optimal Production Planning in a Refinery | 263 |
Optimization of Water Distribution Systems by a Tabu Search Metaheuristic | 279 |
Scatter Search to Generate Diverse MIP Solutions | 299 |
A SimulationBased Policy Iteration Algorithm for Average Cost Unichain Markov Decision Processes | 161 |
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Common terms and phrases
AMPL analysis tasks applied approach AREMOS assignment problem average cost branch and bound components computational consider construction corresponding CPLEX decision maker decision trees declared suffixes defined denote differential cost ECB constraints elements evaluation exam example feasible Figure flow genetic algorithm Global Optimization Glover heuristic implementation infeasible initial inspection integer interface Lagrangean Lagrangean/surrogate Laguna linear programming LP relaxation mathematical model mathematical programming memory meta-heuristics methods metrics node nonbasic objective function objective function value obtained Operations Research optimum P₁ parameters partition permutation Persistent Attractiveness pipe points policy iteration problem instances procedure Queen process reactive tabu search Ring Network Design rough set SBPI Scatter Search Section simulated simulated annealing solution vector solve solver SPSS stationary policy step structure subset Table tabu search techniques unichain update variables visual