Applying a Two-Stage Heuristic Algorithm to the Vehicle Routing Problem of A Cold-Chain Distribution Center

碩士 === 德明財經科技大學 === 物流管理系 === 101 === The Taiwan chain restaurant industry has developed vigorously in recent years. The subjects of this case were famous dumpling and fried dumpling chain stores. If the deliver service quality could be efficiently improved to satisfy the requirements of the chain...

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Bibliographic Details
Main Authors: Yu-Wen Chen, 陳鈺汶
Other Authors: Ku-Kuang Chang
Format: Others
Language:zh-TW
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/63692119669693204338
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Summary:碩士 === 德明財經科技大學 === 物流管理系 === 101 === The Taiwan chain restaurant industry has developed vigorously in recent years. The subjects of this case were famous dumpling and fried dumpling chain stores. If the deliver service quality could be efficiently improved to satisfy the requirements of the chain store owner as well as the cost of delivery could be efficiently reduced while expanding the chain store rapidly, the competition advantages of the business could be enhanced and endless business opportunities created accordingly. In many industries, “Vehicle Routing Problems, VRP” is a common problem. Since the subject company needs to deliver the materials by the time as required, the basic VRP has become a Vehicle Routing Problems with Time Windows, VRPTW. The study adopted a two-stage algorithm, which based on the genetic algorithms (GA) combined with the K-means method for solving the distribution in supply chain. Taking the subject company as example, after dividing customer groups by distances via K-means method in first stage, the GA was applied to calculate the sorting results of groups in second stage. According the experimental results, the two-stage algorithm combining the genetic algorithms with (GA) the K-means method is feasible and efficient. The calculation under GA for groups separated by K-means could significantly improve the solving time and efficiency. The results will be faster and more efficient as comparing to the results derived simply from GA.