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Titlebook: Meta-Heuristics; Advances and Trends Stefan Vo?,Silvano Martello,Catherine Roucairol Book 1999 Springer Science+Business Media New York 19

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書目名稱Meta-Heuristics
副標(biāo)題Advances and Trends
編輯Stefan Vo?,Silvano Martello,Catherine Roucairol
視頻videohttp://file.papertrans.cn/632/631194/631194.mp4
圖書封面Titlebook: Meta-Heuristics; Advances and Trends  Stefan Vo?,Silvano Martello,Catherine Roucairol Book 1999 Springer Science+Business Media New York 19
描述.Meta-Heuristics: Advances and Trends in Local SearchParadigms for. .Optimizations. comprises a carefully refereedselection of extended versions of the best papers presented at theSecond Meta-Heuristics Conference (MIC 97). The selected articlesdescribe the most recent developments in theory and applications ofmeta-heuristics, heuristics for specific problems, and comparativecase studies. The book is divided into six parts, grouped mainly bythe techniques considered. The extensive first part with twelve paperscovers tabu search and its application to a great variety ofwell-known combinatorial optimization problems (including theresource-constrained project scheduling problem and vehicle routingproblems). In the second part we find one paper where tabu search andsimulated annealing are investigated comparatively and two paperswhich consider hybrid methods combining tabu search with geneticalgorithms. The third part has four papers on genetic and evolutionaryalgorithms. Part four arrives at a new paradigm withinmeta-heuristics. The fifth part studies the behavior of parallel localsearch algorithms mainly from a tabu search perspective. The finalpart examines a great variety of additi
出版日期Book 1999
關(guān)鍵詞Constraint satisfaction; actuator; algorithm; algorithms; combinatorial optimization; evolutionary algori
版次1
doihttps://doi.org/10.1007/978-1-4615-5775-3
isbn_softcover978-1-4613-7646-0
isbn_ebook978-1-4615-5775-3
copyrightSpringer Science+Business Media New York 1999
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Neighborhood Search Algorithm for the Guillotine Non-Oriented Two-Dimensional Bin Packing Problem minimized. We show how some classical greedy algorithms given in the literature for the case where no rotation is allowed can be adapted to our problem; in addition, an original heuristic algorithm is presented. We then introduce a tabu search approach to the problem, and analyze its average performance through extensive computational testing.
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Candidate List and Exploration Strategies for Solving 0/1 Mip Problems Using a Pivot Neighborhoodd is quite costly to evaluate, particularly for large problems. Special attention is also given to the tableau based neighborhood structure. General guidelines based on computational experience are reported.
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