A heuristic algorithm approach to reverse logistics network for resolving splits in location/allocation problems

• Main Authors: Guo-Shuo Wu, 吳國碩
• Other Authors: Chwen-Tzeng Su
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/68282674462485938192

碩士 === 雲林科技大學 === 工業工程與管理研究所碩士班 === 96 === Recycling conscious has been rising in recent years, and action taken frequently is setting a collection point, and it has been shown in some past research. In facility location-allocation that only addresses on p-median location model but not is pq-median. Therefore, for conforming to practical situation in this research, in limited capacity of collection points and centralized return centers, bringing up nonlinear mixed-integer programming model by pq-median location model reduces total cost in reverse logistics because of the connection among the best quantities and places of collection points and centralized return center, holding period for each collection point, and customers, collection points and centralized return center. Figuring out location allocation problem in reverse logistics by building heuristic algorithm compared with genetic algorithm for solving quality and solving time; this report proves that heuristic algorithm is better than genetic algorithm in three different illustrations. In sensitivity analysis, further demonstration to the maximum of holding period is for decision maker reference.