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大连海洋大学学报  2019, Vol. 34 Issue (5): 746-751    DOI: 10.16535/j.cnki.dlhyxb.2018-210
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基于改进蚁群算法的冰鲜水产品配送路径优化方法研究
田鸽, 薛冬娟, 梁斌, 温凤仙, 李鹏飞
大连海洋大学 机械与动力工程学院,辽宁 大连 116023

Distribution route and its optimization of chilled fishery products

TIAN Ge,XUE Dong-juan*,LIANG Bin, WEN Feng-xian, LI Peng-fei
College of Mechanical and Power Engineering, Dalian Ocean University, Dalian 116023, China
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摘要 为研究冰鲜水产品最优配送路径的优化方法,在传统蚁群算法基础上提出一种改进的蚁群算法,先后分别采用局部最优和全局最优两种方式对传统蚁群算法的信息素更新方式加以扩大至最优解寻觅范围,并对启发因子的函数定义范围加以扩展至初始节点,利用2-opt算法进行局部优化。实例仿真结果表明,在相同配送条件下,改进后的蚁群算法与避圈法、传统蚁群算法相比较,其配送时间分别缩短31.64%和8.15%,其配送路径长度分别缩短21.89%和16.94%。研究表明,改进的蚁群算法可用于冰鲜水产品最优配送路径的计算,该方法可在实际应用中有效提高冰鲜水产品的物流运输效率。
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田鸽
薛冬娟
梁斌
温凤仙
李鹏飞
关键词:  冰鲜水产品  改进蚁群算法  路径优化  信息素更新    
Abstract: A distribution routing optimization scheme is sought to the special requirements for cost control and delivery time of chilled fishery products in this paper. Firstly, the orientation of initialization pheromone is guided based on the traditional ant colony algorithm, and local optimization and global optimization to modify the updating of pheromone are adopted successively in order to expand the search range of optimal solution. Then the function definition of the heuristic factor is extended to the initial node and the 2-opt algorithm is introduced for local optimization to increasing its convergence speed. Finally, the simulation results showed that the improved algorithm shortened distribution path length and distribution time obviously.
Key words:  chilled fishery product    improved ant colony algorithm    path optimization    pheromone update
               出版日期:  2019-10-10      发布日期:  2019-10-10      期的出版日期:  2019-10-10
中图分类号:  TP312  
基金资助: 辽宁省教育厅科研项目(L201628);辽宁省海洋渔业厅科研项目(201722)
引用本文:    
田鸽, 薛冬娟, 梁斌, 温凤仙, 李鹏飞. 基于改进蚁群算法的冰鲜水产品配送路径优化方法研究[J]. 大连海洋大学学报, 2019, 34(5): 746-751.
TIAN Ge, XUE Dong-juan, LIANG Bin, WEN Feng-xian, LI Peng-fei.

Distribution route and its optimization of chilled fishery products

. Journal of Dalian Ocean University, 2019, 34(5): 746-751.
链接本文:  
https://xuebao.dlou.edu.cn/CN/10.16535/j.cnki.dlhyxb.2018-210  或          https://xuebao.dlou.edu.cn/CN/Y2019/V34/I5/746
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