Case Study on Optimal Routing in Logistics Network by Priority-based Genetic Algorithm
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- Wang Xiaoguang
- Waseda University, Graduate School of Information, Production and Systems
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- Lin Lin
- Waseda University, Graduate School of Information, Production and Systems
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- Gen Mitsuo
- Waseda University, Graduate School of Information, Production and Systems
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- Shiota Mitsushige
- Nippon Steel Transportation Co., Ltd.
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Abstract
Recently, research on logistics caught more and more attention. One of the important issues on logistics system is to find optimal delivery routes with the least cost for products delivery. Numerous models have been developed for that reason. However, due to the diversity and complexity of practical problem, the existing models are usually not very satisfying to find the solution efficiently and convinently.<br>In this paper, we treat a real-world logistics case with a company named ABC Co. ltd., in Kitakyusyu Japan. Firstly, based on the natures of this conveyance routing problem, as an extension of transportation problem (TP) and fixed charge transportation problem (fcTP) we formulate the problem as a minimum cost flow (MCF) model. Due to the complexity of fcTP, we proposed a priority-based genetic algorithm (pGA) approach to find the most acceptable solution to this problem. In this pGA approach, a two-stage path decoding method is adopted to develop delivery paths from a chromosome. We also apply the pGA approach to this problem, and compare our results with the current logistics network situation, and calculate the improvement of logistics cost to help the management to make decisions. Finally, in order to check the effectiveness of the proposed method, the results acquired are compared with those come from the two methods/ software, such as LINDO and CPLEX.
Journal
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- IEEJ Transactions on Electronics, Information and Systems
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IEEJ Transactions on Electronics, Information and Systems 127 (1), 10-16, 2007
The Institute of Electrical Engineers of Japan
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Details 詳細情報について
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- CRID
- 1390001204604917888
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- NII Article ID
- 10018660554
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- NII Book ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL BIB ID
- 8623606
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- Text Lang
- en
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed