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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhenkun Wang Qingfu Zhang Hui Li |
| Copyright Year | 2015 |
| Description | Author affiliation: Key Lab. of Intell. Perception & Image Understanding of Minist. of Educ. of China, Xidian Univ., Xi'an, China (Zhenkun Wang) || Dept. of Comput. Sci., City Univ. of Hong Kong, Kowloon, China (Qingfu Zhang) || Sch. of Math. & Stat., Xi'an Jiaotong Univ., Xi'an, China (Hui Li) |
| Abstract | This paper studies how to use two reproduction operators with different characteristics for balancing the convergence and the diversity in MOEA/D. We consider two operators. One is a differential evolution and polynomial mutation, and the other is a neighbor learning and inversion mutation. We show that these two operators have different search abilities. Then we propose a scheme to use these two operators in our recently proposed MOEA/D-GR framework. We test the proposed algorithm on some benchmark problems to demonstrate its effectiveness. |
| Starting Page | 2849 |
| Ending Page | 2854 |
| File Size | 305196 |
| Page Count | 6 |
| File Format | |
| e-ISBN | 9781479986972 |
| DOI | 10.1109/SMC.2015.496 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-10-09 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Convergence Sociology Statistics Optimization Linear programming Indexes Computer science diversity Multiobjective optimization MOEA/D reproduction convergence |
| Content Type | Text |
| Resource Type | Article |
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