Further note on the probabilistic constraint handling

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dc.contributor.authorCiftcioglu O.
dc.contributor.authorBittermann M.S.
dc.contributor.authorDatta R.
dc.date.accessioned2024-07-12T22:00:06Z
dc.date.available2024-07-12T22:00:06Z
dc.date.issued2016en_US
dc.departmentMaltepe Üniversitesi, Rektörlüken_US
dc.descriptionIEEE Computational Intelligence Society (CIS)en_US
dc.description2016 IEEE Congress on Evolutionary Computation, CEC 2016 -- 24 July 2016 through 29 July 2016 -- -- 124911en_US
dc.description.abstractA robust probabilistic constraint handling approach in the framework of joint evolutionary-classical optimization has been presented earlier. In this work, the theoretical foundations of the method are presented in detail. The method is known as bi-objective method, where the conventional penalty function approach is implemented. The present work highlights the dynamic variation of the commensurate penalty parameter for each objective treated as constraint. It is shown that the constraint parameters collectively define the right slope of the tangent as to the optimal front during the search. The robust and sustained convergence throughout the search up to micro level in the range of 10 -10 or beyond is explained. The work here is presented as a further note in connection with the previous publication, where the subtle theoretical considerations and their details had been omitted for the sake of detailed results of the experiments demonstrating the effective working of the approach. In contrast to the implementation-centered reporting of the previous work, this work can be considered as a description of the detailed probabilistic basis underlying the previous work. Therefore, this study is of great importance to let the researchers conveniently gain the insight into the work and its implications reported earlier. © 2016 IEEE.en_US
dc.identifier.doi10.1109/CEC.2016.7744284
dc.identifier.endpage3908en_US
dc.identifier.isbn9.78151E+12
dc.identifier.scopus2-s2.0-85008263812en_US
dc.identifier.startpage3901en_US
dc.identifier.urihttps://dx.doi.org/10.1109/CEC.2016.7744284
dc.identifier.urihttps://hdl.handle.net/20.500.12415/9035
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2016 IEEE Congress on Evolutionary Computation, CEC 2016en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzKY06938
dc.subjectConstrained optimizationen_US
dc.subjectEvolutionary algorithmen_US
dc.subjectMultiobjective optimizationen_US
dc.subjectProbabilistic modelingen_US
dc.titleFurther note on the probabilistic constraint handlingen_US
dc.typeConference Object
dspace.entity.typePublication

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