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  • 标题:Fast Mesh-Sorting in Multi-objective Optimization ∗
  • 本地全文:下载
  • 作者:Narendra Patel ; Nitin Padhiyar
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2015
  • 卷号:48
  • 期号:8
  • 页码:936-941
  • DOI:10.1016/j.ifacol.2015.09.090
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractA single parameter based fast mesh-sorting is proposed in this work. The single parameter algorithm as compared to non-dominated sorting eliminates the classification of the population into non-dominated fronts and calculating crowding distance. The proposed one parameter approach also provides flexibility of choosing any probability based selection operator. On the other hand, non-dominated sorting approach can only use tournament selection directly. We have considered Zitzler-Deb-Thieles (ZDT) test functions to test computational and convergence capabilities of proposed algorithm. The performance of the proposed algorithm is compared with conventional Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and NSGA-II with a recent fast corner-sort algorithm. We have also considered optimal control of fed-batch reactor as Multi-objective optimization application.
  • 关键词:KeywordsMulti-objective OptimizationGenetic AlgorithmNSGAmesh-sort
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