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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Sato, H. |
| Copyright Year | 2015 |
| Description | Author affiliation: Fac. of Inf. & Eng., Univ. of Electro-Commun., Chofu, Japan (Sato, H.) |
| Abstract | Several recent studies showed the effectiveness of MOEA/D for many-objective optimization. However, MOEA/D was originally proposed not for many-objective optimization but for multi-objective optimization. Therefore, its algorithm causes several problems in many-objective optimization. MOEA/D uses the neighbor mating, and neighbors are determined by the user-defined neighbors' size T. For each weight vector which determines a search direction in the objective space, MOEA/D calculates distances to all weights and find T nearest weights as its neighbors. However, the number of weights having the same distance is increased as the number of objectives is increased, and MOEA/D faces the difficulty to determine neighbors by the neighbors' size T in many-objective optimization. Also, especially for the extreme weights to search the extreme objective function values, weights far from them are included as their neighbors. It causes a negative effect on the search of the extreme objective values. To overcome these problems and enhance the search performance of MOEA/D by improving its algorithm appropriately for many-objective optimization, in this work we focus on the handling of neighbors and propose an improved MOEA/D including the constant-distance based neighbors and the tournament selection based on the scalarizing function values. We use many-objective knapsack problems with 2-8 objectives and compare the search performances of the conventional MOEA/D, the improved MOEA/D and NSGA-III. As the results, we show that the improved MOEA/D achieves higher search performance than the conventional MOEA/D and NSGA-III by improving the diversity of the obtained solutions in the objective space. |
| Starting Page | 2867 |
| Ending Page | 2874 |
| File Size | 1244603 |
| Page Count | 8 |
| File Format | |
| e-ISBN | 9781479974924 |
| DOI | 10.1109/CEC.2015.7257245 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-05-25 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Search problems Optimization Indexes Bismuth Linear programming Sociology Statistics |
| Content Type | Text |
| Resource Type | Article |
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