2022 Fiscal Year Final Research Report
Co-evolutionary Metaheuristics for Multi-Objective Optimization Considering Diverse Operating Conditions in Trucking
| Project/Area Number |
20K04961
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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 | Kindai University |
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Principal Investigator |
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| Project Period (FY) |
2020-04-01 – 2023-03-31
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| Keywords | 配送計画 / 積み付け / トラック輸送 / 遺伝的アルゴリズム |
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| Outline of Final Research Achievements |
In this study, we focused on the truck transportation business, and in order to enable decision-making support that takes into account various operating conditions during transportation, we proposed a multi-objective metaheuristic for loading packages onto trucks and determining the route to visit customers. Specifically, targeting the delivery of packages for end users, we proposed a genetic algorithm-based optimization method for solving the package loading problem for trucks and vehicle routing problem. For validating the effectiveness of the proposed method, we conducted the numerical experiment.
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| Free Research Field |
生産システム工学
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| Academic Significance and Societal Importance of the Research Achievements |
本研究は，トラックによる荷物の配送を対象に，配送巡回経路の最適化のみならず，トラックへの荷物の積み付けをも同時に考慮する最適化手法を提案した．巡回経路最適化，積み付け最適化のいずれも求解困難な組み合わせ最適化問題であり，これらを統一した枠組みの中で同時に求解する点に，本研究の学術的かつ社会的意義があると言える．貨物輸送量の増加は今後も益々増加することが考えられる反面，輸送業界は慢性的に人手不足であり，これを解決する一つの手段として輸送効率向上は必須であり，本研究の提案法は輸送効率向上のための基礎技術として貢献できる．
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