| Project/Area Number |
15K12460
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Social systems engineering/Safety system
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| Research Institution | Nagoya University |
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Principal Investigator |
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| Research Collaborator |
WU Wei
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| Project Period (FY) |
2015-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2016: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | ロバスト最適化 / 組合せ最適化 |
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| Outline of Final Research Achievements |
Most of the optimization algorithms are designed under the assumption that we are given a fixed set of input data for the problem to be solved. However, in real-world situations, input data may contain uncertainty and/or we may not have accurate estimates of the problem parameters when the optimization decision is taken. For this reason, it is important to devise algorithms which obtain robust solutions that are not very sensitive to fluctuations in the input parameters.
We proposed heuristic and exact algorithms for the generalized assignment problem under min-max regret criterion, and those for the knapsack problem under Gamma-robust criterion, analyzing their theoretical properties. We also conducted computational experiments to evaluate their performance.
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| Academic Significance and Societal Importance of the Research Achievements |
計画段階で別の解を選んでいればもっとうまくいったのに，と後悔することのないようにするためには，入力データがどのように変動しても大きく損することのないような解を得る必要がある．そのような変動の組合せは無数にあるため，それらすべてに対して解の良し悪しを判断することは困難である．そのような変動の組合せのすべてを列挙することなく変動に強い解を得るために，数理的な手法を導入することでこれを可能にし，そのような仕組みを取り入れたアルゴリズムを開発した．代表的な組合せ最適化問題に対して提案手法を適用し，その有効性を示した．
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