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Multiobjective Differential Evolution Algorithm with Multiple Trial Vectors
Joint Authors
Source
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-09-12
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
This paper presents a multiobjective differential evolution algorithm with multiple trial vectors.
For each individual in the population, three trial individuals are produced by the mutation operator.
The offspring is produced by using the crossover operator on the three trial individuals.
Good individuals are selected from the parent and the offspring and then are put in the intermediate population.
Finally, the intermediate population is sorted according to the Pareto dominance relations and the crowding distance, and then the outstanding individuals are selected as the next evolutionary population.
Comparing with the classical multiobjective optimization algorithm NSGA-II, the proposed algorithm has better convergence, and the obtained Pareto optimal solutions have better diversity.
American Psychological Association (APA)
Gao, Yuelin& Liu, Junmei. 2012. Multiobjective Differential Evolution Algorithm with Multiple Trial Vectors. Abstract and Applied Analysis،Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-451628
Modern Language Association (MLA)
Gao, Yuelin& Liu, Junmei. Multiobjective Differential Evolution Algorithm with Multiple Trial Vectors. Abstract and Applied Analysis No. 2012 (2012), pp.1-12.
https://search.emarefa.net/detail/BIM-451628
American Medical Association (AMA)
Gao, Yuelin& Liu, Junmei. Multiobjective Differential Evolution Algorithm with Multiple Trial Vectors. Abstract and Applied Analysis. 2012. Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-451628
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-451628