Development of a new multi-objective evolutionary algorithm to advance large-scale many-objective optimization
Project/Area Number |
23500276
|
Research Category |
Grant-in-Aid for Scientific Research (C)
|
Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
Sensitivity informatics/Soft computing
|
Research Institution | Shinshu University |
Principal Investigator |
|
Co-Investigator(Kenkyū-buntansha) |
TANAKA Kiyoshi 信州大学, 工学部, 教授 (20273071)
|
Project Period (FY) |
2011 – 2013
|
Project Status |
Completed (Fiscal Year 2013)
|
Budget Amount *help |
¥5,070,000 (Direct Cost: ¥3,900,000、Indirect Cost: ¥1,170,000)
Fiscal Year 2013: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2012: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2011: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
|
Keywords | 進化計算 / 大規模多数目的最適化 / 適応選択 / 目的空間分割 / 目的関数の次元数削減 / 実世界の問題への応用 / 並列化 / 目的空間分割アルゴリズム / 多目的アルゴリズムのハイブリッド化 / 適応化 |
Research Abstract |
This work proposes an effective evolutionary algorithm for many-objective optimization. It clarifies the importance of population size, the relevance of non-disruptive recombination, and the scalability in large-scale many-objective optimization. The algorithm reduces its parameters and increases its reliability for different problems and population sizes by using two adaptive methods during selection. The effectiveness of epsilon dominance mappings to search sets of optimal solutions with desired distributions is shown and new methods based on conflict information among objectives are proposed for space partitioning. The proposed algorithm is verified in real-world optimization problems. Namely, the proposed algorithm is applied to optimize the trajectory of JAXA's DESTINY mission spacecraft.
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Report
(4 results)
Research Products
(85 results)