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URN etd-0905106-183606 Statistics This thesis had been viewed 2756 times. Download 950 times. Author Yu-Kun Chen Author's Email Address No Public. Department Information Management Year 2005 Semester 2 Degree Master Type of Document Master's Thesis Language Chinese&English Page Count 115 Title Using Genetic Algorithm for Better Route Arrangement Keyword Vehicle Routing Problem Genetic Algorighms Traveling Salesman Problem Traveling Salesman Problem Genetic Algorighms Vehicle Routing Problem Abstract The problem of a real case of route arrangement caused by the needs of delivering goods directly to home is discussed in this paper. Normally the route is arranged by a driver according to his experience. However, such arrangement may not be appropriate. As a matter of fact, an accurate distance matrix is established by performing geographical information software, PowerMap. An efficient delivering spot planning strategy is proposed in this paper to make the analysis more practical and reasonable. The problem is solved by adopting a Genetic Algorithm (GA), which is carried out by using commercial software, Evolver. We also discuss the parameter setting effect on GA simulation performance. We adopt both the classic parameter settings suggested by past articles and the software default setting concept, and also observe the difference between two parameter setting concepts. The result shows that the best route given by GA is much better than that arranged from the driver’s experience, and can shorten the original distance for about 17% every day. Advisor Committee Cheng-Liang Yang - advisor
none - co-chair
none - co-chair
Files Date of Defense 2005-06-29 Date of Submission 2006-09-06