Variable Neighborhood Search with Permutation Distance for QAP

QAP is a famous NP-Hard[1] combinatorial optimization problem. Many theoretical and real-life problems could be modeled as it. VNS is a recent metaheuristic and shows good performance in dealing with QAP[2]. In this paper, a new concept distance called permutation distance is proposed and exploited in detail. With permutation distance ready, we combine the hamming distance with it and propose a group of new neighborhood structures in QAP for VNS. Numerical tests running on the standard benchmark library QAPLIB[3] show that this approach would dramatically improve the performance of VNS for QAP. It surpasses some famous metaheuristics and belongs to the most efficient metaheuristics for QAP.

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