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dc.contributor.authorChugh, Tinkle
dc.contributor.authorSindhya, Karthik
dc.contributor.authorMiettinen, Kaisa
dc.contributor.authorJin, Yaochu
dc.contributor.authorKratky, Tomas
dc.contributor.authorMakkonen, Pekka
dc.date.accessioned2017-08-09T10:35:41Z
dc.date.available2017-08-09T10:35:41Z
dc.date.issued2017
dc.identifier.citationChugh, T., Sindhya, K., Miettinen, K., Jin, Y., Kratky, T., & Makkonen, P. (2017). Surrogate-assisted evolutionary multiobjective shape optimization of an air intake ventilation system. In <i>2017 IEEE Congress on Evolutionary Computation (CEC)</i> (pp. 1541-1548). IEEE. <a href="https://doi.org/10.1109/CEC.2017.7969486" target="_blank">https://doi.org/10.1109/CEC.2017.7969486</a>
dc.identifier.otherCONVID_27113047
dc.identifier.otherTUTKAID_74406
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/55055
dc.description.abstractWe tackle three different challenges in solving a real-world industrial problem: formulating the optimization problem, connecting different simulation tools and dealing with computationally expensive objective functions. The problem to be optimized is an air intake ventilation system of a tractor and consists of three computationally expensive objective functions. We describe the modeling of the system and its numerical evaluation with a commercial software. To obtain solutions in few function evaluations, a recently proposed surrogate-assisted evolutionary algorithm K-RVEA is applied. The diameters of four different outlets of the ventilation system are considered as decision variables. From the set of nondominated solutions generated by K-RVEA, a decision maker having substance knowledge selected the final one based on his preferences. The final selected solution has better objective function values compared to the baseline solution of the initial design. A comparison of solutions with K-RVEA and RVEA (which does not use surrogates) is also performed to show the potential of using surrogates.
dc.language.isoeng
dc.publisherIEEE
dc.relation.ispartof2017 IEEE Congress on Evolutionary Computation (CEC)
dc.subject.otheroptimization
dc.subject.otherresistance
dc.subject.othernumerical models
dc.subject.othersoftware
dc.titleSurrogate-assisted evolutionary multiobjective shape optimization of an air intake ventilation system
dc.typeconferenceObject
dc.identifier.urnURN:NBN:fi:jyu-201707243355
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineMathematical Information Technologyen
dc.type.urihttp://purl.org/eprint/type/ConferencePaper
dc.date.updated2017-07-24T12:15:05Z
dc.relation.isbn978-1-5090-4601-0
dc.type.coarconference paper
dc.description.reviewstatuspeerReviewed
dc.format.pagerange1541-1548
dc.type.versionacceptedVersion
dc.rights.copyright© 2017 IEEE. This is a final draft version of an article whose final and definitive form has been published by IEEE. Published in this repository with the kind permission of the publisher.
dc.rights.accesslevelopenAccessfi
dc.relation.conferenceIEEE Congress on Evolutionary Computation
dc.subject.ysolineaarinen optimointi
dc.subject.ysoilmanvaihto
dc.subject.ysohydraulijärjestelmät
jyx.subject.urihttp://www.yso.fi/onto/yso/p15483
jyx.subject.urihttp://www.yso.fi/onto/yso/p5431
jyx.subject.urihttp://www.yso.fi/onto/yso/p25132
dc.relation.doi10.1109/CEC.2017.7969486


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