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dc.contributor.authorBurak, Jan
dc.contributor.authorMengshoel, Ole Jakob
dc.date.accessioned2022-04-06T08:52:32Z
dc.date.available2022-04-06T08:52:32Z
dc.date.created2022-01-20T12:37:34Z
dc.date.issued2021
dc.identifier.isbn978-1-4503-8351-6
dc.identifier.urihttps://hdl.handle.net/11250/2990112
dc.description.abstractIn this paper, we describe underlying concepts related to the problem of jacket design as well as previous research on jacket design optimization. Motivated by the complexity of the problem, including the multiple objectives typically involved, we develop a novel multi-objective genetic algorithm, NSGA-J, which is tailored to jacket design optimization. NSGA-J is based on the prominent Non-Dominated Sorting Genetic Algorithm (NSGA-II), but tailors it to the problem of designing jackets. Experimentally, we study a cloud-based implementation of NSGA-J and present our results and experiences. The paper ends with a discussion of lessons learned and sketches opportunities for future research. We hope to inspire future work on complex applications of structural design optimization including jacket design optimization.en_US
dc.language.isoengen_US
dc.publisherAssociation for Computing Machinery (ACM)en_US
dc.relation.ispartofGECCO '21: Genetic and Evolutionary Computation Conference, Companion Volume
dc.titleA Multi-Objective Genetic Algorithm for Jacket Optimizationen_US
dc.typeChapteren_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber1549-1556en_US
dc.identifier.doi10.1145/3449726.3463150
dc.identifier.cristin1986134
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.qualitycode1


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