Volume 42, Number 1, January-March 2008Cooperative methods for multiobjective optimization
|Page(s)||3 - 33|
|Published online||21 February 2008|
MEMOTS: a memetic algorithm integrating tabu search for combinatorial multiobjective optimization
Laboratory of Mathematics & Operational Research, Faculté Polytechnique de Mons, 9, rue de Houdain, 7000 Mons, Belgium; email@example.com
Accepted: 30 October 2007
We present in this paper a new multiobjective memetic algorithm scheme called MEMOX. In current multiobjective memetic algorithms, the parents used for recombination are randomly selected. We improve this approach by using a dynamic hypergrid which allows to select a parent located in a region of minimal density. The second parent selected is a solution close, in the objective space, to the first parent. A local search is then applied to the offspring. We experiment this scheme with a new multiobjective tabu search called PRTS, which leads to the memetic algorithm MEMOTS. We show on the multidimensional multiobjective knapsack problem that if the number of objectives increase, it is preferable to have a diversified research rather using an advanced local search. We compare the memetic algorithm MEMOTS to other multiobjective memetic algorithms by using different quality indicators and show that the performances of the method are very interesting.
Mathematics Subject Classification: 90C29 / 90C59
Key words: Combinatorial multiobjective optimization / hybrid metaheuristic / memetic algorithm / Tabu Search / Knapsack
© EDP Sciences, ROADEF, SMAI, 2008
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