| Project/Area Number |
18K04625
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 25010:Social systems engineering-related
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| Research Institution | Kansai University |
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Principal Investigator |
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| Project Period (FY) |
2018-04-01 – 2023-03-31
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| Project Status |
Completed (Fiscal Year 2022)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2020: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2019: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | 組合せ最適化 / 輸送システム / アルゴリズム / 最適化モデル / 数理モデル |
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| Outline of Final Research Achievements |
In this study, we first constructed an optimization model. Specifically, in order to respond flexibly to data fluctuations, we constructed an optimization model that can predict data fluctuations and easily change plans in response to changes, as well as a model that finds efficient routes and takes customer satisfaction into account.
Next, optimization algorithms were developed. Concretely, multiple approaches were developed depending on the scale of the problem, and a heuristic solution method was developed for the problem with multiple numbers of transport vehicles. Numerical simulations were then conducted to verify that the developed algorithms worked.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究は，近年のIT技術の発展に伴い現代社会が要求している答えと，数理としての最適化問題の解との差を縮める役割を果たす．その意味で学術的に重要な課題であると考える．また，コミュニティバスの例におけるバス・バス停・住民を，それぞれ輸送車・営業所・顧客と置き換えると，宅配などの物流業者の輸送システムにも応用できる．
また学術的にも，最適化問題でありながら最適解を敢えて放棄して，解の変更のしやすさを追求するという点で新しい発想であり，非常に特色のあるアプローチであると思われる．
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