Evolutionary optimization

著者

書誌事項

Evolutionary optimization

edited by Ruhul Sarker, Masoud Mohammadian, Xin Yao

（International series in operations research & management science, 48）

Kluwer Academic Publishers, c2002

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注記

Includes bibliographical references and index

"ISOR 48"--Back cover

内容説明・目次

内容説明

Evolutionary computation techniques have attracted increasing att- tions in recent years for solving complex optimization problems. They are more robust than traditional methods based on formal logics or mathematical programming for many real world OR/MS problems. E- lutionary computation techniques can deal with complex optimization problems better than traditional optimization techniques. However, most papers on the application of evolutionary computation techniques to Operations Research /Management Science (OR/MS) problems have scattered around in different journals and conference proceedings. They also tend to focus on a very special and narrow topic. It is the right time that an archival book series publishes a special volume which - cludes critical reviews of the state-of-art of those evolutionary com- tation techniques which have been found particularly useful for OR/MS problems, and a collection of papers which represent the latest devel- ment in tackling various OR/MS problems by evolutionary computation techniques. This special volume of the book series on Evolutionary - timization aims at filling in this gap in the current literature. The special volume consists of invited papers written by leading - searchers in the field. All papers were peer reviewed by at least two recognised reviewers. The book covers the foundation as well as the practical side of evolutionary optimization.

目次

  • Preface. Contributing Authors. Part I: Introduction. 1. Conventional Optimization Techniques
  • M.S. Hillier, F.S. Hillier. 2. Evolutionary Computation
  • Xin Yao. Part II: Single Objective Optimization. 3. Evolutionary Algorithms and Constrained Optimization
  • Z. Michalewicz, M. Schmidt. 4. Constrained Evolutionary Optimization
  • T. Runarsson, Xin Yao. Part III: Multi-Objective Optimization. 5. Evolutionary Multiobjective Optimization
  • C.A. Coello Coello. 6. MEA for Engineering Shape Design
  • K. Deb, T. Goel. 7. Assessment Methodologies for MEAs
  • R. Saker, C.A. Coello Coello. Part IV: Hybrid Algorithms. 8. Hybrid Genetic Algorithms
  • J.A. Joines, M.G. Kay. 9. Combining choices of heuristics
  • P. Ross, E. Hart. 10. Nonlinear Constrained Optimization
  • B.W. Wah, Yi-Xin Chen. Part V: Parameter Selection in EAs. 11. Parameter Selection
  • Z. Michalewicz, et al. Part VI: Application of EAs to Practical Problems. 12. Design of Production Facilities. 13. Virtual Population and Acceleration Techniques. Part VII: Application of EAs to Theoretical Problems. 14. Methods for the analysis of EAs on pseudo-boolean functions
  • I. Wegener. 15. A GA Heuristic For Finite Horizon POMDPs
  • A.Z.-Z. Lin, et al. 16. Finding Good k-Tree Subgraphs
  • E. Ghashghai, R.L. Rardin. Index.

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