基于元胞小生境遗传算法的物流配送路径优化  

Logistics Distribution Route Optimization Based on Cellular Niche Genetic Algorithm

作　　者：朱大林[1] 詹腾[1] 张屹[1] 刘铮[1] 

机构地区：[1]三峡大学机械与材料学院,宜昌443002

出　　处：《组合机床与自动化加工技术》2013年第1期121-125,共5页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：国家自然科学基金项目(51275274)

摘　　要：现在物流业面临着小批量和多动态的需求,对物流配送路径进行优化显得越来越重要。然而,解决此优化问题的核心是设计一种快速有效地优化方法,基于此,文章在经典元胞遗传算法的基础上,引入小生境技术,得到了一种元胞小生境遗传算法,使算法具有较好的多样性保持能力。将该算法应用于带有时间窗的车辆路径问题的求解当中,并针对该问题设计了一种顺序逆转交叉算子,结果表明,新算法相对于经典元胞遗传算法和小生境遗传算法能更好的避免陷于"早熟",所得结果精度更高,是解决物流配送路径优化问题的有效算法。Since the present logistics industry is in limited quantities and with many factors of dynamic changes, logistic distribution route optimization is becoming increasingly important. However, the key to solve this problem is to design a quick and effective optimization method. On this basis, this paper proposes a new cellular niche genetic algorithm based on canonical cellular genetic algorithm by introducing niche technology, which can maintain the population diversity very well. The proposed algorithm is then applied to solving the vehicle routing problem with time-window and an order-reversing crossover opera- tor is designed. The results indicate that in comparing with the canonical cellular genetic algorithms and niche genetic algorithms the use of new algorithm can help to avoid pre-mature more effectively, the resuits gained is of higher accuracy, and it is an efficient algorithm in solving the logistic distribution route optimization problems.

关 键 词：路径优化 元胞结构 遗传算法 小生境技术 

分 类 号：TH16[机械工程—机械制造及自动化] TG65[金属学及工艺—金属切削加工及机床]