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dc.contributor.authorPodkopaev, Dmitry
dc.contributor.authorMiettinen, Kaisa
dc.contributor.authorOjalehto, Vesa
dc.date.accessioned2021-11-03T14:01:24Z
dc.date.available2021-11-03T14:01:24Z
dc.date.issued2021
dc.identifier.citationPodkopaev, D., Miettinen, K., & Ojalehto, V. (2021). An Approach to the Automatic Comparison of Reference Point-Based Interactive Methods for Multiobjective Optimization. <i>IEEE Access</i>, <i>9</i>, 150037-150048. <a href="https://doi.org/10.1109/access.2021.3123432" target="_blank">https://doi.org/10.1109/access.2021.3123432</a>
dc.identifier.otherCONVID_101729530
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/78488
dc.description.abstractSolving multiobjective optimization problems means finding the best balance among multiple conflicting objectives. This needs preference information from a decision maker who is a domain expert. In interactive methods, the decision maker takes part in an iterative process to learn about the interdependencies and can adjust the preferences. We address the need to compare different interactive multiobjective optimization methods, which is essential when selecting the most suited method for solving a particular problem. We concentrate on a class of interactive methods where a decision maker expresses preference information as reference points, i.e., desirable objective function values. Comparison of interactive methods with human decision makers is not a straightforward process due to cost and reliability issues. The lack of suitable behavioral models hampers creating artificial decision makers for automatic experiments. Few approaches to automating testing have been proposed in the literature; however, none are widely used. As a result, empirical performance studies are scarce for this class of methods despite its popularity among researchers and practitioners.We have developed a new approach to replace a decision maker to automatically compare interactive methods based on reference points or similar preference information. Keeping in mind the lack of suitable human behavioral models, we concentrate on evaluating general performance characteristics. Such an evaluation can partly address the absence of any tests and is appropriate for screening methods before more rigorous testing. We have implemented our approach as a ready-to-use Python module and illustrated it with computational examples.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartofseriesIEEE Access
dc.rightsCC BY 4.0
dc.subject.otherdecision making
dc.subject.otherinteractive systems
dc.subject.othermultiobjective optimization
dc.subject.otheroptimization
dc.subject.otheroptimization methods
dc.subject.othertesting
dc.titleAn Approach to the Automatic Comparison of Reference Point-Based Interactive Methods for Multiobjective Optimization
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202111035513
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineLaskennallinen tiedefi
dc.contributor.oppiaineMultiobjective Optimization Groupfi
dc.contributor.oppiaineComputational Scienceen
dc.contributor.oppiaineMultiobjective Optimization Groupen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange150037-150048
dc.relation.issn2169-3536
dc.relation.volume9
dc.type.versionpublishedVersion
dc.rights.copyright© 2021 the Authors
dc.rights.accesslevelopenAccessfi
dc.subject.ysomonitavoiteoptimointi
dc.subject.ysointeraktiivisuus
dc.subject.ysooptimointi
dc.subject.ysotestaus
dc.subject.ysopäätöksentukijärjestelmät
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p32016
jyx.subject.urihttp://www.yso.fi/onto/yso/p10823
jyx.subject.urihttp://www.yso.fi/onto/yso/p13477
jyx.subject.urihttp://www.yso.fi/onto/yso/p8471
jyx.subject.urihttp://www.yso.fi/onto/yso/p27803
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1109/access.2021.3123432
dc.type.okmA1


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