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Addressing Unequal Area Facility Layout Problems with the Coral Reef Optimization algorithm with Substrate Layers

2020-08Journal article Restricted access
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dc.contributor.authorGarcia-Hernandez, L.
dc.contributor.authorGarcia-Hernandez, J. A.
dc.contributor.authorSalas-Morera, L.
dc.contributor.authorCarmona-Munoz, C.
dc.contributor.authorAlghamdi, N. S.
dc.contributor.authorValente de Oliveira, José
dc.contributor.authorSalcedo-Sanz, S.
dc.date.accessioned2021-06-24T11:35:22Z
dc.date.available2021-06-24T11:35:22Z
dc.date.issued2020-08
dc.description.abstractThe Unequal Area Facility Layout Problem (UA-FLP) is a relevant task in industrial manufacturing, in which the disposition of a number of facilities (or departments) in a manufacturing system must be obtained, under several optimization criteria and different constraints. The UA-FLP is a hard optimization problem, in which traditional optimization techniques do not obtain good results. Thus, it has been successfully tackled with different heuristics and meta-heuristics in the last years. In this work we address the UA-FLP with a multi-method ensemble approach, the Coral Reefs Optimization algorithm with Substrate Layers (CRO-SL). It is a novel multi-method evolutionary algorithm that encourages the evolution of several searching procedures at the same time over a single population. The CRO-SL has been previously applied to very difficult optimization problems, obtaining excellent performance. In this case, we adapt the CRO-SL to the UA-FLP, by means of increasing the diversity generation within the algorithm, which is helpful to improve the exploration of the searching space, avoiding to fall into local minima. Specifically, we propose to include several reproduction mechanisms (adapted to the UA-FLP) within each substrate of the algorithm, which will highly increase the diversity generation in the CRO-SL. An exhaustive experimental study of the CRO-SL performance in a large number of UA-FLP instances is carried out, including a comparison with the state-of-the-art algorithms for this problem. We will show the ability of the CRO-SL to reach or surpass the best-known solutions in most of the tested UA-FLP cases.
dc.description.sponsorshipPrincess Nourah bint Abdulrahman UniversityPrincess Nourah Bint Abdulrahman University
dc.description.sponsorshipSpanish Ministry of Economy, Industry and Competitiveness, Government of Spain [TIN2017-85887-C2-2-P]
dc.description.sponsorshipJunta de Andalucia, SpainJunta de Andalucia [1265277 MD A1]
dc.description.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.doi10.1016/j.engappai.2020.103697
dc.identifier.issn0952-1976
dc.identifier.urihttp://hdl.handle.net/10400.1/16420
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier
dc.subjectUnequal Area Facility Layout Problem
dc.subjectCoral Reefs Optimization
dc.subjectFacility Layout
dc.subjectMeta-heuristics
dc.subjectBio-inspired algorithms
dc.subject.otherAutomation & Control Systems
dc.titleAddressing Unequal Area Facility Layout Problems with the Coral Reef Optimization algorithm with Substrate Layers
dc.typejournal article
dspace.entity.typePublication
oaire.citation.startPage103697
oaire.citation.titleEngineering Applications of Artificial Intelligence
oaire.citation.volume93
person.familyNameLUÍS VALENTE DE OLIVEIRA
person.givenNameJOSÉ
person.identifier.ciencia-id1F12-C1D3-7717
person.identifier.orcid0000-0001-5337-5699
rcaap.rightsrestrictedAccess
rcaap.typearticle
relation.isAuthorOfPublicationbb726e73-690c-4a33-822e-c47bdac3035b
relation.isAuthorOfPublication.latestForDiscoverybb726e73-690c-4a33-822e-c47bdac3035b

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