2010 Fiscal Year Final Research Report
Development of effective evolutionary algorithms for many-objective optimization
| Project/Area Number |
21800021
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| Research Category |
Grant-in-Aid for Research Activity Start-up
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| Allocation Type | Single-year Grants |
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| Research Field |
Intelligent informatics
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| Research Institution | The University of Electro-Communications |
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Principal Investigator |
SATO Hiroyuki The University of Electro-Communications, 大学院・情報理工学研究科, 助教 (60550978)
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| Project Period (FY) |
2009 – 2010
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| Keywords | 多数目的最適化 / 多目的最適化 / 進化型アルゴリズム |
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| Research Abstract |
To develop effective multi-objective evolutionary algorithms (MOEAs) for many-objective optimization problems which optimize more than four objective functions simultaneously, in this work we have developed a novel MOEA partially applying Pareto dominance and a method to self-control the dominance area of solutions. Also, to encourage the solutions search in many-objectives problems, we have developed a method of crossover controlling the number of crossed genes. The result of performance verification using benchmark problems revealed that proposed methods significantly improve the search performance of MOEA on many-objective optimization problems.
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