A Neighborhood Combining Approach in GRASP's Local Search for Quadratic Assignment Problem Solutions

Erika Granillo Martinez, Rogelio González Velázquez, María Beatriz Bernabé Loranca, José Luis Martínez Flores


In this paper we describe a study for the search of solutions of the combinatorial optimization problem Quadratic Assignment Problem (QAP) through the implementation of a Greedy Randomized Adaptive Procedure Search (GRASP) and have been compared with the best solutions known in the literature, obtaining robust results in terms of the value of the objective function and the execution time. Also a comparison with the ant algorithm is presented with the aim of comparing the meta-heuristic. The most important contribution of this paper is the use of the combination of different neighborhood structures in the GRASP improvement phase. The experiment was performed for a set of test instances available in QAPLIB. The QAP belongs to the Np-hard class whereby this approximation algorithm is implemented.


Meta-heuristics, NP-hard, neighborhood structure, combinatorial optimization, local search, GRASP, QAP

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