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An interactive heuristic method for multi-objective combinatorial optimization
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DOI：10.1016/S0305-0548(99)00109-4.png)
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Abstract
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We have previously developed an adaptation of the simulated annealing for multi-objective combinatorial optimization (MOCO) problems to construct an approximation of the efficient set of such problem. In order to deal with large-scale problems, we transform this approach to propose an interactive procedure. The method is tested on the multi-objective knapsack problem and the multi-objective assignment problem. Scope and purpose Meta-heuristics methods are intensively used with success to solve optimization problems and especially combinatorial problems (Pirlot. EJOR 1996;92:493-511). In the case of a single objective problem, such methods compute an approximation to the unique optimal solution. Recently, some meta-heuristics have been adapted to treat multi-objective problems. These methods construct an approximation of the set of all efficient solutions. For large-scale 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 paper. (C) 2000 Elsevier Science Ltd. All rights reserved.
Keywords:
multi-objective programming
combinatorial optimization
knapsack problem
assignment problem
simulated annealing
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