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Advances in Multi-Objective Nature Inspired Computing

Buch | Hardcover
XV, 195 Seiten
2010
Springer Berlin (Verlag)
978-3-642-11217-1 (ISBN)
CHF 224,65 inkl. MwSt
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The purpose of this book is to collect contributions that deal with the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems. Such a collection intends to provide an overview of the state-of-the-art developments in this field, with the aim of motivating more researchers in operations research, engineering, and computer science, to do research in this area. As such, this book is expected to become a valuable reference for those wishing to do research on the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems.

Multi-Objective Combinatorial Optimization: Problematic and Context.- Approximating Pareto-Optimal Sets Using Diversity Strategies in Evolutionary Multi-Objective Optimization.- On the Velocity Update in Multi-Objective Particle Swarm Optimizers.- Approaching Dynamic Multi-Objective Optimization Problems by Using Parallel Evolutionary Algorithms.- ParadisEO-MOEO: A Software Framework for Evolutionary Multi-Objective Optimization.- The Multiobjective Traveling Salesman Problem: A Survey and a New Approach.- On the Performance of Local Search for the Biobjective Traveling Salesman Problem.- A Bi-objective Metaheuristic for Disaster Relief Operation Planning.

Erscheint lt. Verlag 4.2.2010
Reihe/Serie Studies in Computational Intelligence
Zusatzinfo XV, 195 p.
Verlagsort Berlin
Sprache englisch
Maße 155 x 235 mm
Gewicht 1060 g
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Mathematik / Informatik Mathematik Angewandte Mathematik
Technik
Schlagworte algorithm • combinatorial optimization • Computational Intelligence • Evolution • evolutionary algorithm • Hardcover, Softcover / Technik/Allgemeines, Lexika • Heuristics • Heuristik • Informatik • Metaheuristic • Multi-Objective Optimization • Natural Computing • Nature-Inspired Computing • Operations Research • Optimization
ISBN-10 3-642-11217-X / 364211217X
ISBN-13 978-3-642-11217-1 / 9783642112171
Zustand Neuware
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