[1]王勇,毛海军,刘静.带时间窗的物流配送区域划分模型及其算法[J].东南大学学报(自然科学版),2010,40(5):1077-1083.[doi:10.3969/j.issn.1001-0505.2010.05.037] 　Wang Yong,Mao Haijun,Liu Jing.Logistics distribution region partition model with time windows and its algorithms[J].Journal of Southeast University (Natural Science Edition),2010,40(5):1077-1083.[doi:10.3969/j.issn.1001-0505.2010.05.037] 点击复制 带时间窗的物流配送区域划分模型及其算法() 分享到： var jiathis_config = { data_track_clickback: true };

40

2010年第5期

1077-1083

2010-09-20

文章信息/Info

Title:
Logistics distribution region partition model with time windows and its algorithms

Author(s):
School of Transportation,Southeast University,Nanjing 210096, China

Keywords:

TP301.6;TP18
DOI:
10.3969/j.issn.1001-0505.2010.05.037

Abstract:
Tobacco industry has large-scale customers, customers’ demand is not fixed, the maximum travel distance of distribution vehicles is limited and customers’ delivery time is not fixed. Based on these features the logistics distribution region is divided into different distribution units by cluster methods, and integer programming is applied to choose unfixed transfer stations. Finally on the basis of fixed cost and variable cost and delay cost with time windows of distribution units, a mathematical programming model is established to minimize the cost of logistics distribution network considering multi-product, multi-client, time constraints and other factors. An EPSO-GA(extended particle swarm optimization-genetic algorithms)is also presented to solve the model. In this algorithm distance and time constraints are added into evaluation function, and selective interaction between the algorithms is designed, therefore, it provides a higher global and local search capability. The simulation results show that the hybrid algorithm can solve distribution region partition problems which include large-scale distribution points. It is more effective than MPSO(multi-phases particle swarm optimization algorithm),GA(genetic algorithms),PSO(particle swarm optimization)and GA-PSO(genetic algorithm-particle swarm optimization)algorithms.

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