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Theoretical Aspects of Local Search [electronic resource] / by Wil Michiels, Jan Korst, Emile Aarts.

Por: Michiels, Wil [author.]Colaborador(es): Korst, Jan [author.] | Aarts, Emile [author.]Tipo de material: TextoTextoSeries Monographs in Theoretical Computer Science, An EATCS SeriesEditor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007Descripción: VIII, 238 p. 70 illus. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783540358541Trabajos contenidos: SpringerLink (Online service)Tema(s): Computer science | Information theory | Computer software | Artificial intelligence | Mathematical optimization | Computer Science | Mathematics of Computing | Algorithm Analysis and Problem Complexity | Theory of Computation | Artificial Intelligence (incl. Robotics) | Optimization | Operations Research/Decision TheoryFormatos físicos adicionales: Sin títuloClasificación CDD: 004.0151 Clasificación LoC:QA76.9.M35Recursos en línea: de clik aquí para ver el libro electrónico
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Springer eBooksResumen: Local search has been applied successfully to a diverse collection of optimization problems. It's appreciated for its basic conceptual foundation, its general applicability, and its power to serve as a source for new search paradigms. The typical characteristics of combinatorial optimization problems to which local search can be applied, its relation to complexity theory, and the combination with randomized search features have led to a wealth of interesting theoretical results. However, these results are scattered throughout the literature. This is the first book that presents a large collection of theoretical results in a consistent manner, thus providing the reader with a coherent overview of the achievements obtained so far, but also serving as a source of inspiration for the development of novel results in the challenging field of local search.
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Basic Examples -- Indirect Solution Representations -- Properties of Neighborhood Functions -- Performance Guarantees -- Time Complexity -- Metaheuristics -- Asymptotic Convergence of Simulated Annealing.

Local search has been applied successfully to a diverse collection of optimization problems. It's appreciated for its basic conceptual foundation, its general applicability, and its power to serve as a source for new search paradigms. The typical characteristics of combinatorial optimization problems to which local search can be applied, its relation to complexity theory, and the combination with randomized search features have led to a wealth of interesting theoretical results. However, these results are scattered throughout the literature. This is the first book that presents a large collection of theoretical results in a consistent manner, thus providing the reader with a coherent overview of the achievements obtained so far, but also serving as a source of inspiration for the development of novel results in the challenging field of local search.

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