Multiobjective Tabu Search Optimization

Ricardo Pedro Beausoleil

ISBN 10: 6202249862 / ISBN 13: 9786202249867

Editore: Editorial Académica Española Jan 2018, 2018

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Neuware -The field of metaheuristics for different multiobjective optimization problems is a rapidly growing field of research. A multiobjective optimization task considers several conflicting objectives simultaneously. There are at least two equally important tasks: an optimization task for finding a set of optimal solutions, called Pareto optimal solutions and a decision-making task for choosing a single most preferred solution. The objective of this book is to show how tabu search procedures can be used to solve difficult problems in a multiobjective framework. The first chapter, is devoted to present different basic method to solve multiobjective optimization tasks. The second chapter, presents multiobjective tabu/scatter search architecture with preference information based on reference points for problems of continuous nature. The third chapter, introduces an adaptation of a multiobjective tabu/scatter search to deal with nonlinear discrete, mixed-integer constrained engineering optimization problems. This book is useful for researchers in the field of metaheuristic optimization, graduate in computer science, operation research, management science and other engineering disciplines.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch. Codice articolo 9786202249867

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Titolo: Multiobjective Tabu Search Optimization

Casa editrice: Editorial Académica Española Jan 2018

Data di pubblicazione: 2018

Legatura: Taschenbuch

Condizione: Neu

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Riassunto:

The field of metaheuristics for different multiobjective optimization problems is a rapidly growing field of research. A multiobjective optimization task considers several conflicting objectives simultaneously. There are at least two equally important tasks: an optimization task for finding a set of optimal solutions, called Pareto optimal solutions and a decision-making task for choosing a single most preferred solution. The objective of this book is to show how tabu search procedures can be used to solve difficult problems in a multiobjective framework. The first chapter, is devoted to present different basic method to solve multiobjective optimization tasks. The second chapter, presents multiobjective tabu/scatter search architecture with preference information based on reference points for problems of continuous nature. The third chapter, introduces an adaptation of a multiobjective tabu/scatter search to deal with nonlinear discrete, mixed-integer constrained engineering optimization problems. This book is useful for researchers in the field of metaheuristic optimization, graduate in computer science, operation research, management science and other engineering disciplines.