Chance-Constrained Optimization Formulation for Ship Conceptual Design: A Comparison of Metaheuristic Algorithms

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dc.contributor.authorKůdela, Jakubcs
dc.coverage.issue11cs
dc.coverage.volume12cs
dc.date.issued2023-11-03cs
dc.description.abstractThis paper presents a new chance-constrained optimization (CCO) formulation for the bulk carrier conceptual design. The CCO problem is modeled through the scenario design approach. We conducted extensive numerical experiments comparing the convergence of both canonical and state-of-the-art metaheuristic algorithms on the original and CCO formulations and showed that the CCO formulation is substantially more difficult to solve. The two best-performing methods were both found to be differential evolution-based algorithms. We then provide an analysis of the resulting solutions in terms of the dependence of the distribution functions of the unit transportation costs and annual cargo capacity of the ship design on the probability of violating the chance constraints.en
dc.formattextcs
dc.format.extent17cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationComputers. 2023, vol. 12, issue 11, 17 p.en
dc.identifier.doi10.3390/computers12110225cs
dc.identifier.issn2073-431Xcs
dc.identifier.orcid0000-0002-4372-2105cs
dc.identifier.other186908cs
dc.identifier.researcheridP-7327-2018cs
dc.identifier.scopus56769626500cs
dc.identifier.urihttp://hdl.handle.net/11012/245110
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofComputerscs
dc.relation.urihttps://www.mdpi.com/2073-431X/12/11/225cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/2073-431X/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectchance-constrained optimizationen
dc.subjectship conceptual designen
dc.subjectmetaheuristicsen
dc.subjectevolutionary computationen
dc.subjectnumerical optimizationen
dc.titleChance-Constrained Optimization Formulation for Ship Conceptual Design: A Comparison of Metaheuristic Algorithmsen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-186908en
sync.item.dbtypeVAVen
sync.item.insts2025.02.03 15:47:54en
sync.item.modts2025.01.17 16:50:45en
thesis.grantorVysoké učení technické v Brně. Fakulta strojního inÅŸenÃœrství. Ústav automatizace a informatikycs
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