Metaheuristic Optimization Via Memory And Evolution
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Metaheuristic Optimization via Memory and Evolution
Author | : Cesar Rego |
Publisher | : Springer Science & Business Media |
Total Pages | : 472 |
Release | : 2006-03-30 |
Genre | : Business & Economics |
ISBN | : 0387236678 |
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Tabu Search (TS) and, more recently, Scatter Search (SS) have proved highly effective in solving a wide range of optimization problems, and have had a variety of applications in industry, science, and government. The goal of Metaheuristic Optimization via Memory and Evolution: Tabu Search and Scatter Search is to report original research on algorithms and applications of tabu search, scatter search or both, as well as variations and extensions having "adaptive memory programming" as a primary focus. Individual chapters identify useful new implementations or new ways to integrate and apply the principles of TS and SS, or that prove new theoretical results, or describe the successful application of these methods to real world problems.