Development of a parallel method with learning for large-scale optimization, based on intelligent agents
| Project/Area Number |
09650438
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
System engineering
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| Research Institution | Chiba University |
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Principal Investigator |
HIRATA Hironori Chiba Univ., Graduate School of Science and Technology, Professor, 大学院・自然科学研究科, 教授 (60111415)
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| Co-Investigator(Kenkyū-buntansha) |
KOAKUTSU Seiichi Chiba Univ., Graduate School of Science and Technology, Associate Professor, 大学院・自然科学研究科, 助教授 (70241940)
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| Project Period (FY) |
1997 – 1998
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| Project Status |
Completed (Fiscal Year 1998)
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| Budget Amount *help |
¥3,400,000 (Direct Cost: ¥3,400,000)
Fiscal Year 1998: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 1997: ¥2,600,000 (Direct Cost: ¥2,600,000)
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| Keywords | optimization method / learning cellular automaton / layout / learning automaton / combinatorial optimization / network / optimization / evolution / 組合せ最適化 / 遺伝 |
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| Research Abstract |
The project has studied the development of a new parallel optimization method based on intelligent agents and applied it to combinatorial optimization problems.
Practically speaking, we use learning cellular automata as intelligent agents. Learning cellular automata makes it possible to search a global minimum in the cost landscape with high accuracy.
The proposed method has the ability of massive parallel computation using a parallel computer.
We applied it to combinatorial optimization problems and verified the effectiveness and the usefulness of the proposed method.
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Report
(3 results)
Research Products
(18 results)
