A hybrid genetic/immune strategy to tackle the multiobjective quadratic assignment problem
نویسندگان
چکیده
The Genetic Immune Strategy for Multiple Objective Optimization (GISMOO) is a hybrid algorithm for solving multiobjective problems. The performance of this approach has been assessed using a classical combinatorial multiobjective optimization benchmark: the multiobjective 0/1 knapsack problem (MOKP) [1] and two-dimensional unconstrained multiobjective problems (ZDT) [2]. This paper shows that the GISMOO algorithm can also efficiently solve the multiobjective quadratic assignment problem (mQAP). A performance comparison carried out using well-known published algorithms and shows GISMOO to advantage.
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