First published 2 September 2013
A hybrid genetic/immune strategy to tackle the multiobjective quadratic assignment problem
Arnaud Zinflou, Caroline Gagné, Marc Gravel
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)  and two-dimensional unconstrained multiobjective problems (ZDT) . 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.