Fast Solution to Large-Scale Multiobjective Optimization Problems using Parallel Ant Colony Optimization in Dynamic Environment
| Project/Area Number |
23500169
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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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| Research Field |
Intelligent informatics
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| Research Institution | University of Tsukuba |
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Principal Investigator |
KANOH Hitoshi 筑波大学, システム情報系, 教授 (40251045)
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| Project Period (FY) |
2011 – 2013
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| Project Status |
Completed (Fiscal Year 2013)
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| Budget Amount *help |
¥3,250,000 (Direct Cost: ¥2,500,000、Indirect Cost: ¥750,000)
Fiscal Year 2013: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2012: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2011: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | 群知能 / アントコロニー最適化法 / 配送問題 |
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| Research Abstract |
In this research, we presented a solution to real-world delivery problems for home delivery services where a large number of roads exist in cities and the traffic on the roads rapidly changes with time. The methodology for finding the shortest-travel-time tour includes a hybrid meta-heuristic that combines ant colony optimization (ACO) with Dijkstra algorithm, a search technique that uses both real-time traffic and predicted traffic, and a way to use a real-world road map and measured traffic in Japan. We proposed a hybrid ACO for RWDPs that used a MAX-MIN Ant System (MMAS) and proposed a method to improve the search rate of MMAS. Since traffic on roads changes with time, the search rate is important in RWDPs. Experimental results using a map of central Tokyo and historical traffic data indicate that the proposed method can find a better solution than conventional methods.
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Report
(4 results)
Research Products
(21 results)
