Advances in Computational and Stochastic Optimization, Logic Programming, and Heuristic Search

Advances in Computational and Stochastic Optimization, Logic Programming, and Heuristic Search : Interfaces in Computer Science and Operations Research

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Description

Computer Science and Operations Research continue to have a synergistic relationship and this book - as a part of the Operations Research and Computer Science Interface Series - sits squarely in the center of the confluence of these two technical research communities. The research presented in the volume is evidence of the expanding frontiers of these two intersecting disciplines and provides researchers and practitioners with new work in the areas of logic programming, stochastic optimization, heuristic search and post-solution analysis for integer programs.
The chapter topics span the spectrum of application level. Some of the chapters are highly applied and others represent work in which the application potential is only beginning. In addition, each chapter contains expository material and reviews of the literature designed to enhance the participation of the reader in this expanding interface.
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Product details

  • Hardback | 312 pages
  • 164.1 x 243.8 x 25.1mm | 712.15g
  • Dordrecht, Netherlands
  • English
  • 1998 ed.
  • 38 Illustrations, black and white; VII, 312 p. 38 illus.
  • 0792380789
  • 9780792380788

Table of contents

Preface. 1. Constraint Satisfaction Methods; J.N. Hooker. 2. Extending a General-Purpose Algebraic Modeling Language to Combinatorial Optimization: A Logic Programming Approach; R. Fourer. 3. Disjunctive Programming and Cooperating Solvers; K. McAloon, et al. 4. Mixed and Integer Programming Post-Solution Analysis; H.J. Greenberg. 5. Stochastic Knapsack Problem; D.P. Morton, R.K. Wood. 6. Sample-Path Solutions for Simulation Optimization Problems and Stochastic Variational Inequalities; G. Gurkan, et al. 7. Play Selection in American Football: A Case Study in Neuro-Dynamic Programming; S.D. Patek, D.P. Bertsekas. 8. Tabu Search Candidate List Strategies in Scheduling; B. Rangaswamy, et al. 9. GA's and Surrogate Constraints for MCKPs; C. Haul, S. Voss. 10. Introduction to Genetic Heuristics and Vehicle Routing Problems with Complex Constraints; S.R. Thangiah, P. Petrovic. 11. A Genetic Algorithm for the Clustered Traveling Salesman Problem with a Prespecified Order on the Clusters; J.-Y. Potvin, F. Guertin. 12. A New Algorithm for the Site-Dependent Vehicle Routing Problem; I-Ming Chao, et al.
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