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.