| Presentation | 1997/5/23 Multiobjective Optimization using Neighborhood Model Genetic Algorithms Masahiro Murakawa, Shuji Yoshizawa, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | We propose a method of multiobjective optimization using genetic alogorithms. The proposed method doesn't reduce the objective vector to a scalar value, but finds a set of Pareto-optimal solutions using neighborhood model genetic algorithms. In the neighborhood model, population members are held in a grid. The range of genetic interaction is limited to population members in the immediate neighboring grid nodes. This maintains the diversity of the chromosomes. The results of numerical experiments show that the proposed method can find a set of various Pareto-optimal solutions. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Genetic Algorithms / Neighborhood Model / Multiobjective Optimization / Pareto-Optimal Solutions |
| Paper # | NC97-6 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 1997/5/23(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Neurocomputing (NC) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Multiobjective Optimization using Neighborhood Model Genetic Algorithms |
| Sub Title (in English) | |
| Keyword(1) | Genetic Algorithms |
| Keyword(2) | Neighborhood Model |
| Keyword(3) | Multiobjective Optimization |
| Keyword(4) | Pareto-Optimal Solutions |
| 1st Author's Name | Masahiro Murakawa |
| 1st Author's Affiliation | Faculty of Engineering, University of Tokyo() |
| 2nd Author's Name | Shuji Yoshizawa |
| 2nd Author's Affiliation | Faculty of Engineering, University of Tokyo |
| Date | 1997/5/23 |
| Paper # | NC97-6 |
| Volume (vol) | vol.97 |
| Number (no) | 69 |
| Page | pp.pp.- |
| #Pages | 8 |
| Date of Issue | |