Development of an Optimal Code for the Vehicle Dispatch System
| Project/Area Number |
07805039
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
System engineering
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| Research Institution | Ibaraki University |
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Principal Investigator |
HAMAMATSU Yoshio Ibaraki University, Faculty of Engineering, Department of Systems Engineering, Associate Professor, 工学部, 助教授 (70102019)
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| Co-Investigator(Kenkyū-buntansha) |
ASANO Naoki Ibaraki University, Faculty of Engineering, Department of Mechanical Engineering, 工学部, 教授 (40074364)
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| Project Period (FY) |
1995 – 1997
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| Project Status |
Completed (Fiscal Year 1997)
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| Budget Amount *help |
¥2,300,000 (Direct Cost: ¥2,300,000)
Fiscal Year 1997: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 1996: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 1995: ¥900,000 (Direct Cost: ¥900,000)
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| Keywords | multi-route searching problem / NP-complete / vhehcles dispatch system / incremental algorithm / m-TSP / perspective ratio / nearest neighbor method / 車輌ディスパッチシステム / 逐次添加アルゴリズム / 階層分析法 / 車輌ディスパッテシステム / 区間縮小法 |
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| Research Abstract |
The summary of this research results are as follows,
(1) It is necessary to count up all possible combinations of vehicles and customers because of based on the enumerative method which can solve the exact solution. We consider an algorithm which does not use any If-statement using two operators in the program.
(2) If the size of network is increased, the combinations of vehicles and customers are also increased. It is impossible that the micro-computer stores the all combinations. Therefore, the algorithm is improved to decrease the necessary memory capacity using the incremental algorithm.
(3) We propose a new route searching method by which we consider with the geometrical information to solve a large-scale problem. This approximate method is using a sort of evaluation function called the perspective ratio.
(4) If the relationship between two cities are shortest distance each other in the considering area, the same vehicle must visit two cities. It can be decreased the number of cities substantially.
(5) From (3) and (4), the determination of combination with vehicles and customers can be calculated rapidly.
(6) The determination of each vehicle's route is taking quite long time because of the comparison with the distance of route. Therefore, we adopted one of the heuristic search method, the nearest neighbor method. Thus, the calculation time has been decreased.
(7) From the data in compared with the Genetic algorithm and the branch-and-bound method, this proposed algorithm has short calculation time and good precision.
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Report
(4 results)
Research Products
(6 results)
