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Titlebook: Essays and Surveys in Metaheuristics; Celso C. Ribeiro,Pierre Hansen Book 2002 Springer Science+Business Media New York 2002 Analysis.algo

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發(fā)表于 2025-3-21 19:44:35 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Essays and Surveys in Metaheuristics
編輯Celso C. Ribeiro,Pierre Hansen
視頻videohttp://file.papertrans.cn/316/315241/315241.mp4
叢書(shū)名稱Operations Research/Computer Science Interfaces Series
圖書(shū)封面Titlebook: Essays and Surveys in Metaheuristics; Celso C. Ribeiro,Pierre Hansen Book 2002 Springer Science+Business Media New York 2002 Analysis.algo
描述Finding exact solutions to many combinatorial optimization problems in busi- ness, engineering, and science still poses a real challenge, despite the impact of recent advances in mathematical programming and computer technology. New fields of applications, such as computational biology, electronic commerce, and supply chain management, bring new challenges and needs for algorithms and optimization techniques. Metaheuristics are master procedures that guide and modify the operations of subordinate heuristics, to produce improved approx- imate solutions to hard optimization problems with respect to more simple algorithms. They also provide fast and robust tools, producing high-quality solutions in reasonable computation times. The field of metaheuristics has been fast evolving in recent years. Tech- niques such as simulated annealing, tabu search, genetic algorithms, scatter search, greedy randomized adaptive search, variable neighborhood search, ant systems, and their hybrids are currently among the most efficient and robust optimization strategies to find high-quality solutions to many real-life optimiza- tion problems. A very large nmnber of successful applications of metaheuristi
出版日期Book 2002
關(guān)鍵詞Analysis; algorithms; evolutionary algorithm; genetic algorithms; heuristics; metaheuristic; optimization;
版次1
doihttps://doi.org/10.1007/978-1-4615-1507-4
isbn_softcover978-1-4613-5588-5
isbn_ebook978-1-4615-1507-4Series ISSN 1387-666X Series E-ISSN 2698-5489
issn_series 1387-666X
copyrightSpringer Science+Business Media New York 2002
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https://doi.org/10.1007/978-3-662-26537-6to the minimum cost failure immune networks problem is presented. Computational experiments show that the metaheuristic approach outperforms previous simple heuristics. The dependency on starting solution and neighborhood scheme is also analyzed.
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Recent Results in Cancer Researchscribe their commons features and their variants and we give the list of their applications to different combinatorial optimization problems. We also show how the simulated annealing algorithm and the threshold accepting algorithm can be considered as noising methods when the components of the noising methods are properly chosen.
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Selected Topics in Simulated Annealing,on is on theoretical and general results. The presentation of the novel features include generalized convergence results, new performance properties, improved variants, genetic hybrids, and approaches to general mathematical programming models.
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A Simulated Annealing Approach for Minimum Cost Isolated Failure Immune Networks,to the minimum cost failure immune networks problem is presented. Computational experiments show that the metaheuristic approach outperforms previous simple heuristics. The dependency on starting solution and neighborhood scheme is also analyzed.
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978-1-4613-5588-5Springer Science+Business Media New York 2002
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Essays and Surveys in Metaheuristics978-1-4615-1507-4Series ISSN 1387-666X Series E-ISSN 2698-5489
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