Evolutionary Multi-Criterion Optimization
Publication year: 2007
ISBN: 978-3-540-70928-2
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Multicriterion optimization refers to problems with two or more objectives (normally in conflict with each other) which must be simultaneously satisfied. Evolutionary algorithms have been used for solving multicriterion optimization problems for over two decades, gaining an increasing attention from industry. This book included four keynote speakers: Hirotaka Nakayama on aspiration level methods, Kay Chen Tan on large and computationally intensive real-world MO optimization problems, Carlos Fonseca on decision making, and Gary B. Lamont on design of large-scale network centric systems.
Subject: Computer Science, adaptive search, algorithm design, algorithmics, algorithms, approximation, automata, classification, constraint solving, evolutionary algorithm, genetic programming, heuristics, metaheuristics, optimization, programming, visualization
