Solving the quadratic assignment problem with cooperative parallel extremal optimization

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Abstract

Several real-life applications can be stated in terms of the Quadratic Assignment Problem. Finding an optimal assignment is computationally very difficult, for many useful instances. We address this problem using a local search technique, based on Extremal Optimization and present experimental evidence that this approach is competitive. Moreover, cooperative parallel versions of our solver improve performance so much that large and hard instances can be solved quickly.

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Munera, D., Diaz, D., & Abreu, S. (2016). Solving the quadratic assignment problem with cooperative parallel extremal optimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9595, pp. 251–266). Springer Verlag. https://doi.org/10.1007/978-3-319-30698-8_17

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