A Tutorial On the design, experimentation and application of metaheuristic algorithms to real-World optimization problems

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dc.contributor.authorOsaba, Eneko
dc.contributor.authorVillar-Rodriguez, Esther
dc.contributor.authorDel Ser, Javier
dc.contributor.authorNebro, Antonio J.
dc.contributor.authorMolina, Daniel
dc.contributor.authorLaTorre, Antonio
dc.contributor.authorSuganthan, Ponnuthurai N.
dc.contributor.authorCoello Coello, Carlos A.
dc.contributor.authorHerrera, Francisco
dc.contributor.institutionQuantum
dc.contributor.institutionIA
dc.date.issued2021-07
dc.descriptionPublisher Copyright: © 2021 Elsevier B.V.
dc.description.abstractIn the last few years, the formulation of real-world optimization problems and their efficient solution via metaheuristic algorithms has been a catalyst for a myriad of research studies. In spite of decades of historical advancements on the design and use of metaheuristics, large difficulties still remain in regards to the understandability, algorithmic design uprightness, and performance verifiability of new technical achievements. A clear example stems from the scarce replicability of works dealing with metaheuristics used for optimization, which is often infeasible due to ambiguity and lack of detail in the presentation of the methods to be reproduced. Additionally, in many cases, there is a questionable statistical significance of their reported results. This work aims at providing the audience with a proposal of good practices which should be embraced when conducting studies about metaheuristics methods used for optimization in order to provide scientific rigor, value and transparency. To this end, we introduce a step by step methodology covering every research phase that should be followed when addressing this scientific field. Specifically, frequently overlooked yet crucial aspects and useful recommendations will be discussed in regards to the formulation of the problem, solution encoding, implementation of search operators, evaluation metrics, design of experiments, and considerations for real-world performance, among others. Finally, we will outline important considerations, challenges, and research directions for the success of newly developed optimization metaheuristics in their deployment and operation over real-world application environments.en
dc.description.sponsorshipEneko Osaba, Esther Villar-Rodriguez and Javier Del Ser-would like to thank the Basque Government through EMAITEK and ELKARTEK (ref. 3KIA) funding grants. Javier Del Ser-also acknowledges funding support from the Department of Education of the Basque Government (Consolidated Research Group MATHMODE, IT1294-19). Antonio LaTorre acknowledges funding from the Spanish Ministry of Science (TIN2017-83132-C2-2-R). Carlos A. Coello Coello acknowledges support from CONACyT grant no. 2016-01-1920 (Investigación en Fronteras de la Ciencia 2016) and from a SEP-Cinvestav grant (application no. 4). Francisco Herrera and Daniel Molina are partially supported by the project DeepSCOP-Ayudas Fundación BBVA a Equipos de Investigación Científica en Big Data 2018, and the Spanish Ministry of Science and Technology under project TIN2017-89517-P.
dc.description.statusPeer reviewed
dc.identifier.citationOsaba , E , Villar-Rodriguez , E , Del Ser , J , Nebro , A J , Molina , D , LaTorre , A , Suganthan , P N , Coello Coello , C A & Herrera , F 2021 , ' A Tutorial On the design, experimentation and application of metaheuristic algorithms to real-World optimization problems ' , Swarm and Evolutionary Computation , vol. 64 , 100888 . https://doi.org/10.1016/j.swevo.2021.100888
dc.identifier.doi10.1016/j.swevo.2021.100888
dc.identifier.issn2210-6502
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85107680095&partnerID=8YFLogxK
dc.language.isoeng
dc.relation.ispartofSwarm and Evolutionary Computation
dc.relation.projectIDDepartment of Education of the Basque Government, IT1294-19
dc.relation.projectIDSEP-Cinvestav
dc.relation.projectIDEusko Jaurlaritza
dc.relation.projectIDConsejo Nacional de Ciencia y Tecnología, CONACYT, 2016-01-1920
dc.relation.projectIDMinisterio de Ciencia e Innovación, MICINN, TIN2017-83132-C2-2-R
dc.relation.projectIDMinisterio de Ciencia y Tecnología, MICYT, TIN2017-89517-P
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsGood practices
dc.subject.keywordsMetaheuristics
dc.subject.keywordsMethodology
dc.subject.keywordsReal-world optimization
dc.subject.keywordsTutorial
dc.subject.keywordsGeneral Computer Science
dc.subject.keywordsGeneral Mathematics
dc.titleA Tutorial On the design, experimentation and application of metaheuristic algorithms to real-World optimization problemsen
dc.typejournal article
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