| Project/Area Number |
17360424
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Naval and maritime engineering
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| Research Institution | National Maritime Research Institute |
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Principal Investigator |
MAJIMA Takahiro National Maritime Research Institute, Center for Logistics Research, National Maritime Research Institute, Chief Researcher (30392690)
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| Co-Investigator(Kenkyū-buntansha) |
WATANABE Daisuke Faculty of Marine Technology, Tokyo University of Marine Science and Technology, Associate Professor (30435771)
TAKADAMA Keiki Faculty of Electro-Communications, The University of Electro-Communications, Assistant Professor (20345367)
勝原 光治郎 独立行政法人海上技術安全研究所, 物流研究センター, センター長 (20358401)
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| Project Period (FY) |
2005 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥16,570,000 (Direct Cost: ¥15,400,000、Indirect Cost: ¥1,170,000)
Fiscal Year 2007: ¥5,070,000 (Direct Cost: ¥3,900,000、Indirect Cost: ¥1,170,000)
Fiscal Year 2006: ¥4,000,000 (Direct Cost: ¥4,000,000)
Fiscal Year 2005: ¥7,500,000 (Direct Cost: ¥7,500,000)
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| Keywords | Optimized Logistics / Simulation Engineering / Algorithm / Disaster Prevention / Multi-Agent System / シュミレーション工学 / 河川舟運 |
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| Research Abstract |
It is being recognized that transport system with the combination of rivers and ships under disaster circumstance will work effectively as alternative route for the onshore transport system. In fact, the transport operation with ships worked effectively in the Great Hanshin-Awaji earthquake in 1995. Meanwhile, Tokyo metropolitan has been suffering from chronic congestion and heavy commuter rushes for long time. The transport system with rivers and ships is also expected to mitigate such conditions.
This research project focused on the waterbus line network as public transit network and exploited two algorithms and their hybrid algorithm to generate optimized waterbus line network. One is algorithm with knowledge based and the other is that of meta-heuristics. Followings describe research achievements for each algorithm.
1) Algorithm with knowledge based approach Firstly, measures or indices used in the research field regarding to the complex network are applied to grasp the characteristi
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c of transportation network .The target networks are already existing subway, railway network and a hypothetical waterbus network in Tokyo. The analysis results clarified the characteristic of the transportation network and the roll of waterbus network against the already existing network. Using the knowledge of the measures and the framework of the network evolution model actively investigated in the research domain of the complex network, we developed algorithms to generate public transit network for waterbus. Furthermore the algorithm is modified to incorporate the meta-heuristic method to avoid local optimized solutions. It is recognized by comparison of results for benchmark problem that the developed algorithm has potency to outperform the algorithms presented by precedent research work.
2) Algorithm with meta-heuristic approach Fundamental investigation regarding to the LCS (Learning Classifier System) was conducted for understanding its mechanism and features appropriate for the problem to generate bus line network. After the investigations, we decided to employ the Pittsburgh Genetics-Based Machine Learning. In case of disaster situation, it can be considered that the OD(Origin and Destination) demand changes frequently. The developed algorithm works considering several patterns of OD demand and succeeds to yield the robust networks. Less
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