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A BRILS metaheuristic for non-smooth flow-shop problems with failure-risk costs

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dc.contributor.author Ferrer, Alberto
dc.contributor.author Guimarans, Daniel
dc.contributor.author Ramalhinho-Lourenço, Helena
dc.contributor.author Juan, Angel A.
dc.date.accessioned 2021-05-27T07:41:06Z
dc.date.available 2021-05-27T07:41:06Z
dc.date.issued 2016
dc.identifier.citation Ferrer A, Guimarans D, Ramalhinho HR, Juan AA. A BRILS metaheuristic for non-smooth flow-shop problems with failure-risk costs. Expert Syst Appl. 2016 Feb;44:177–86. DOI: 10.1016/j.eswa.2015.09.011
dc.identifier.issn 0957-4174
dc.identifier.uri http://hdl.handle.net/10230/47668
dc.description.abstract This paper analyzes a realistic variant of the Permutation Flow-Shop Problem (PFSP) by considering a non-smooth objective function that takes into account not only the traditional makespan cost but also failure-risk costs due to uninterrupted operation of machines. After completing a literature review on the issue, the paper formulates an original mathematical model to describe this new PFSP variant. Then, a Biased-Randomized Iterated Local Search (BRILS) algorithm is proposed as an efficient solving approach. An oriented (biased) random behavior is introduced in the well-known NEH heuristic to generate an initial solution. From this initial solution, the algorithm is able to generate a large number of alternative good solutions without requiring a complex setting of parameters. The relative simplicity of our approach is particularly useful in the presence of non-smooth objective functions, for which exact optimization methods may fail to reach their full potential. The gains of considering failure-risk costs during the exploration of the solution space are analyzed throughout a series of computational experiments. To promote reproducibility, these experiments are based on a set of traditional benchmark instances. Moreover, the performance of the proposed algorithm is compared against other state-of-the-art metaheuristic approaches, which have been conveniently adapted to consider failure-risk costs during the solving process. The proposed BRILS approach can be easily extended to other combinatorial optimization problems with similar non-smooth objective functions.
dc.description.sponsorship This research has been partially supported by the Spanish Ministry of Economy and Competitiveness, projects MTM2011-29064-C03-02, MTM2014-59179-C2-01 & TRA2013-48180-C3-P, and FEDER. NICTA is funded by the Australian Government through the Department of Communications and the Australian Research Council through the ICT Centre of Excellence Program.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Elsevier
dc.relation.ispartof Expert Systems with Applications. 2016 Feb;44:177–86
dc.rights © Elsevier http://dx.doi.org/10.1016/j.eswa.2015.09.011
dc.title A BRILS metaheuristic for non-smooth flow-shop problems with failure-risk costs
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1016/j.eswa.2015.09.011
dc.subject.keyword Heuristic algorithms
dc.subject.keyword Biased randomization
dc.subject.keyword Iterated Local Search
dc.subject.keyword Scheduling
dc.subject.keyword Flow-shop
dc.subject.keyword Non-smooth objective functions
dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/MTM2011-29064-C03-02
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/MTM2014-59179-C2-01
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/TRA2013-48180-C3-P
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/acceptedVersion


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