An interactive heuristic method for multi-objective combinatorial optimization

We have previously developed an adaptation of the simulated annealing for m ulti-objective combinatorial optimization (MOCO) problems to construct an a pproximation of the efficient set of such problem. In order to deal with la rge-scale problems, we transform this approach to propose an interactive pr ocedure. The method is tested on the multi-objective knapsack problem and t he multi-objective assignment problem. Scope and purpose Meta-heuristics methods are intensively used with success to solve optimiza tion problems and especially combinatorial problems (Pirlot. EJOR 1996;92:4 93-511). In the case of a single objective problem, such methods compute an approximation to the unique optimal solution. Recently, some meta-heuristi cs have been adapted to treat multi-objective problems. These methods const ruct an approximation of the set of all efficient solutions. For large-scal e multi-objective combinatorial problems, the number of efficient solutions may become very large. In order to help a decision maker to make a choice between these solutions, an interactive procedure is developed in this pape r. (C) 2000 Elsevier Science Ltd. All rights reserved.