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    Meta-Heuristics Advances and Trends in Local Search Paradigms for Optimization

    ISBN-10: 1461376467
    ISBN-13: 9781461376460
    Author(s): Stefan Vo�, Silvano Martello, Ibrahim H. Osman, Cath�rine Roucairol
    Description: Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimizations comprises a carefully refereed selection of extended versions of the best papers presented at the Second Meta-Heuristics Conference (MIC 97). The selected articles  More...
    List price: $329.00
    Buy it from: $279.86
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    List Price: $329.00
    Publisher: Springer
    Binding: Paperback
    Pages: 511
    Size: 6.10" wide x 9.25" long x 0.42" tall
    Weight: 1.760
    Language: English

    Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimizations comprises a carefully refereed selection of extended versions of the best papers presented at the Second Meta-Heuristics Conference (MIC 97). The selected articles describe the most recent developments in theory and applications of meta-heuristics, heuristics for specific problems, and comparative case studies. The book is divided into six parts, grouped mainly by the techniques considered. The extensive first part with twelve papers covers tabu search and its application to a great variety of well-known combinatorial optimization problems (including the resource-constrained project scheduling problem and vehicle routing problems). In the second part we find one paper where tabu search and simulated annealing are investigated comparatively and two papers which consider hybrid methods combining tabu search with genetic algorithms. The third part has four papers on genetic and evolutionary algorithms. Part four arrives at a new paradigm within meta-heuristics. The fifth part studies the behavior of parallel local search algorithms mainly from a tabu search perspective. The final part examines a great variety of additional meta-heuristics topics, including neural networks and variable neighbourhood search as well as guided local search. Furthermore, the integration of meta-heuristics with the branch-and-bound paradigm is investigated.

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