Evolutionary Optimization
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Evolutionary Optimization

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Ruhul Sarker
785 g
234x156x24 mm
48, International Series in Operat

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.
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.