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.
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