Abstract
We give an overview of approaches developped by our research team to tackle multi-objective combinatorial optimization problems. We first describe two methodologies — direct methods and two phase methods — to generate the set of efficient solutions; they are illustrated respectively for multi-objective knapsack problem and multi-objective assignment problem. As it is unrealistic to extend these exact methods to problems with more than two criteria or more than a few hundred variables, we then analyze how to adapt metaheuristics to generate an approximation of the set of efficient solutions; the so-called MOSA and MOTAS methods are presented, based respectively on Simulated Annealing and Tabu Search. Finally, we describe the way to apply these heuristics methods in an interactive way.
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Teghem, J. (2002). Methodologies for Solving Multiobjective Combinatorial Optimization Problems. In: Bouyssou, D., Jacquet-Lagrèze, E., Perny, P., Słowiński, R., Vanderpooten, D., Vincke, P. (eds) Aiding Decisions with Multiple Criteria. International Series in Operations Research & Management Science, vol 44. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0843-4_22
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DOI: https://doi.org/10.1007/978-1-4615-0843-4_22
Publisher Name: Springer, Boston, MA
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