A study of stochastic local search algorithms for the biobjective quadratic assignment problem with correlated flow matrices

A study of stochastic local search algorithms for the biobjective quadratic assignment problem with correlated flow matrices

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Article ID: iaor2007451
Country: Netherlands
Volume: 169
Issue: 3
Start Page Number: 943
End Page Number: 959
Publication Date: Mar 2006
Journal: European Journal of Operational Research
Authors: ,
Keywords: heuristics: local search
Abstract:

This paper studies the performance of two stochastic local search algorithms for the biobjective Quadratic Assignment Problem with different degrees of correlation between the flow matrices. The two algorithms follow two fundamentally different ways of tackling multiobjective combinatorial optimization problems. The first is based on the component-wise ordering of the objective value vectors of neighboring solutions, while the second is based on different scalarizations of the objective function vector. Our experimental results suggest that the performance of the algorithms with respect to solution quality and computation time depends strongly on the correlation between the flow matrices. In addition, some variants of these stochastic local search algorithms obtain very good solutions in short computation time.

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