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dc.contributor.authorJariyatantiwait, Chatkaewen_US
dc.contributor.authorฉัตรแก้ว จริยตันติเวทย์en_US
dc.contributor.authorJariyatantiwait, Ponlakiten_US
dc.contributor.authorพลกฤษณ์ จริยตันติเวทย์en_US
dc.date.accessioned2020-08-20T08:52:00Z
dc.date.available2020-08-20T08:52:00Z
dc.date.issued2020-08-20
dc.identifier.urihttp://repository.rmutp.ac.th/handle/123456789/3269
dc.descriptionรายงานวิจัย -- มหาวิทยาลัยเทคโนโลยีราชมงคลพระนคร, 2562en_US
dc.description.abstractDifferential evolution is one of the most efficient optimization algorithms for solving complication problems including single objective, multiobjective and many-objective optimization. It is a stochastic population-based search approach for optimization over the continuous space. The main advantages of differential evolution are simplicity, robustness and high speed of convergence. The Advanced Fuzzy-based Multiobjective Differential Evolution (AFMDE) that exploits three performance metrics, specifically hypervolume, spacing, and maximum spread, to measure the state of the evolution process. The fuzzy inference rules are applied to these metrics in order to adaptively adjust the associated control parameters of the chosen mutation strategy used in AFMDE. The optimization algorithm will stop the evolution process if the number of iterations reaches the stopping criteria which usually is the maximum number of iterations. Then, the optimization algorithm delivers the optimal solution founded. However, sometimes if the maximum number of iterations is not appropriately defined, the found solutions may not be the optimal ones. In case of the optimization algorithm has found the optimal solutions but it must continue the evolution process because the stopping criteria are not met. This can cause unnecessary using of high computational resources and time-consuming. Therefore, this research study proposed the stopping criteria based on performance metrics feedback for AFMDE. The efficiency of the proposed criteria combined with AFMDE is evaluated on the well-known ZDT benchmark test suites.en_US
dc.description.sponsorshipRajamangala University of Technology Phra Nakhonen_US
dc.language.isothen_US
dc.subjectMathematical modelen_US
dc.subjectแบบจำลองทางคณิตศาสตร์en_US
dc.subjectModelen_US
dc.subjectแบบจำลองen_US
dc.subjectFuzzy differential evolutionen_US
dc.subjectฟัซซี่ดิฟเฟอเรนเชียลอิโวลลูชันen_US
dc.titleFuzzy multiobjective differential evolution stopping criteria based on performance metrics feedbacken_US
dc.title.alternativeแบบจำลองของเกณฑ์การหยุดทำงานของฟัซซี่ดิฟเฟอเรนเชียลอิโวลลูชัน แบบหลายวัตถุประสงค์ โดยการป้อนกลับเมตริกสมรรถนะen_US
dc.typeResearch Reporten_US
dc.contributor.emailauthorchatkaew.s@rmutp.ac.then_US
dc.contributor.emailauthorponlakit.j@rmutp.ac.then_US
dc.contributor.emailauthorarit@rmutp.ac.then_US


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