dc.contributor.author Arza E. en_US dc.contributor.author Pérez A. en_US dc.contributor.author Irurozki E. en_US dc.contributor.author Ceberio J. en_US dc.date.accessioned 2020-07-26T14:53:56Z dc.date.available 2020-07-26T14:53:56Z dc.date.issued 2020-07 dc.identifier.uri http://hdl.handle.net/20.500.11824/1138 dc.description.abstract The Quadratic Assignment Problem (QAP) is a well-known permutation-based combinatorial optimization problem with real applications in industrial and logistics environments. Motivated by the challenge that this NP-hard problem represents, it has captured the attention of the optimization community for decades. As a result, a large number of algorithms have been proposed to tackle this problem. Among these, exact methods are only able to solve instances of size $n<40$. To overcome this limitation, many metaheuristic methods have been applied to the QAP. en_US In this work, we follow this direction by approaching the QAP through Estimation of Distribution Algorithms (EDAs). Particularly, a non-parametric distance-based exponential probabilistic model is used. Based on the analysis of the characteristics of the QAP, and previous work in the area, we introduce Kernels of Mallows Model under the Hamming distance to the context of EDAs. Conducted experiments point out that the performance of the proposed algorithm in the QAP is superior to (i) the classical EDAs adapted to deal with the QAP, and also (ii) to the specific EDAs proposed in the literature to deal with permutation problems. dc.description.sponsorship Severo Ochoa SEV-2013-0323 en_US TIN2016-78365-R PID2019-106453GAI00 SVP-2014-068574 TIN2017-82626-R dc.format application/pdf en_US dc.language.iso eng en_US dc.publisher Swarm and Evolutionary Computation en_US dc.relation ES/1PE/TIN2017-82626-R en_US dc.relation EUS/BERC/BERC.2018-2021 en_US dc.relation EUS/ELKARTEK en_US dc.rights info:eu-repo/semantics/openAccess en_US dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/es/ en_US dc.subject Estimation of Distribution Algorithm en_US dc.subject Quadratic Assignment Problem en_US dc.subject Hamming distance en_US dc.subject Mallows Model en_US dc.title Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment Problem en_US dc.type info:eu-repo/semantics/article en_US dc.type info:eu-repo/semantics/acceptedVersion en_US dc.identifier.doi 10.1016/j.swevo.2020.100740 dc.relation.publisherversion https://doi.org/10.1016/j.swevo.2020.100740 en_US
﻿

### This item appears in the following Collection(s)

Except where otherwise noted, this item's license is described as info:eu-repo/semantics/openAccess