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• W2461213408 abstract "Constrained multiobjective optimization arises inmany real-life applications, and is therefore gaining a constantlygrowing attention of the researchers. Constraint handling techniquesdiffer in the way infeasible solutions are evolved inthe evolutionary process along with their feasible counterparts.Our recently proposed threshold based penalty function givesa chance of evolution to infeasible solutions whose constraintviolation is less than a specified threshold value. This paperembeds the threshold based penalty function in the update andreplacement scheme of multi-objective evolutionary algorithmbased on decomposition (MOEA/D) to find tradeoff solutions forconstrained multiobjective optimization problems (CMOPs). Themodified algorithm is tested on CTP-series test instances in termsof the hypervolume metric (HV-metric). The experimental resultsare compared with the two well-known algorithms, NSGA-II andIDEA. The sensitivity of algorithm to the adopted parameters isalso checked. Empirical results demonstrate the effectiveness ofthe proposed penalty function in the MOEA/D framework forCMOPs" @default.
• W2461213408 created "2016-07-22" @default.
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• W2461213408 date "2016-01-01" @default.
• W2461213408 modified "2023-09-27" @default.
• W2461213408 title "Performance of a Constrained Version of MOEA/D on CTP-series Test Instances" @default.
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• W2461213408 doi "https://doi.org/10.14569/ijacsa.2016.070665" @default.
• W2461213408 hasPublicationYear "2016" @default.
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