| Project/Area Number |
08405030
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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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 | KYOTO UNIVERSITY |
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Principal Investigator |
IBARAKI Toshihide Kyoto Univ.Graduate School of Informatics, Professor, 情報学研究科, 教授 (50026192)
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| Co-Investigator(Kenkyū-buntansha) |
MAKINO Kazuhisa Osaka Univ.Grad.School of Engineering Science, Assis.Prof., 基礎工学研究科, 助手 (60294162)
YAGIURA Mutsunori Kyoto Univ.Graduate School of Informatics, Assis.Prof., 情報学研究科, 助手 (10263120)
NAGAMOCHI Hiroshi Kyoto Univ.Graduate School of Informatics, Assoc.Prof., 情報学研究科, 助教授 (70202231)
FUKUSHIMA Masao Kyoto Univ.Graduate School of Informatics, Professor, 情報学研究科, 教授 (30089114)
増山 繁 豊橋技術科学大学, 工学部, 助教授 (60173762)
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| Project Period (FY) |
1996 – 1998
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| Project Status |
Completed (Fiscal Year 1998)
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| Budget Amount *help |
¥23,400,000 (Direct Cost: ¥23,400,000)
Fiscal Year 1998: ¥2,100,000 (Direct Cost: ¥2,100,000)
Fiscal Year 1997: ¥6,700,000 (Direct Cost: ¥6,700,000)
Fiscal Year 1996: ¥14,600,000 (Direct Cost: ¥14,600,000)
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| Keywords | problem solving engine / metaheuristics / CSP (constraint satisfaction problem) / combinatorial optimization / 組合せアルゴリズム / タブ-探索 / 制約充足問題 / 一般化割当問題 / 問題解決 / 組合セアルゴリズム / メタ・ヒューリスティックス |
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| Research Abstract |
The main purpose of this research is to develop general purpose problem solvers for various combinatorial optimization problems. Such solvers may be made possible by resorting to metaheuristic algorithms, which are recently receiving intensive attention. Based on the theoretical and experimental studies on the basic properties of metaheuristic approaches, we implemented several algorithms and conducted extensive numerical experiments on various benchmark problems as well as some problems arising from practical applications.
As platforms for the general purpose problem solvers, we employed CSP (constraint satisfaction problem), GAP (generalized assignment problem), MAX-SAT (maximum satisfiability problem) and RCPSP (resource constrained project scheduling problem). These problems are quite general and can formulate many important problems which we frequently encounter in practice. Judging from our computational experiments, the metaheuristic codes we developed appear to be very useful in a wide variety of applications.
Also included in this research are studies of structured problems, such as graph and network structures, scheduling problems, and nonlinear optimization structures.
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