| Project/Area Number |
10205206
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| Research Category |
Grant-in-Aid for Scientific Research on Priority Areas (B)
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| Allocation Type | Single-year Grants |
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| Research Institution | Tokyo university of mercantile marine |
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Principal Investigator |
KUBO Mikio Tokyo university of mercantile marine, associate professor, 助教授 (60225191)
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| Co-Investigator(Kenkyū-buntansha) |
MIYAMOTO Yuichiro Tokyo university of mercantile marine, research associate, 助手 (20323850)
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| Project Period (FY) |
1998 – 2000
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| Project Status |
Completed (Fiscal Year 2001)
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| Budget Amount *help |
¥5,700,000 (Direct Cost: ¥5,700,000)
Fiscal Year 2000: ¥2,100,000 (Direct Cost: ¥2,100,000)
Fiscal Year 1999: ¥2,200,000 (Direct Cost: ¥2,200,000)
Fiscal Year 1998: ¥1,400,000 (Direct Cost: ¥1,400,000)
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| Keywords | combinatorial optimization / vehicle routing / scheduling / algorithm / NP-困難 / 発見的アルゴリズム / メタ解法 / アルゴリズム工学 |
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| Research Abstract |
We developed meta-heuristics for combinatorial optimization problems and implemented these meta-heuristics with those investigated data structures. We mainly deal with the vehicle routing and the machine scheduling. We presented our research results in many international conferences. The algorithms developed in our research process are open as demo programs (maximum clique, graph partition and channel assignment) in the Algorithm Database that is one of the main results of the research project.
In relation to the vehicle routing, we developed fast algorithm of neighbor search appeared in the meta-heuristics for the vehicle routing with soft time windows that is very important in business practice and in research interest.
We deal with the inventory routing. In the inventory routing, delivery costs and inventory cost are simultaneously optimized. We developed effective algorithm for the inventory routing by using dynamic programming and cross-opt improvement. We also reported computational experiments. The experiments show that the inventory routing reduces total cost about 40%.
We also deal with the scheduling problem. In algorithms for the job-shop scheduling problem, interval consistency tests are known to be effective to narrowing search areas. The tests are naturally extensive to the resource constraint project-scheduling problem and very useful in scheduling. We developed a fast algorithm for the input-or-output test that is one of the interval consistency tests. We reduced the time complexity from O(n^4) to O(n^2log^2n) of the input-or-output test by using the balanced binary tree and heap structures.
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