蚂蚁算法在配送运输问题上的路径优化研究
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摘要
针对实际配送运输情况,路径的优化不仅是要符合路径最短,还要满足时间最短、成本最低等条件,论文在蚂蚁算法的基础上,提出对相关系数以及局部最优改进的路径计算方法,并利用AtuoCAD证,结果表明了论文算法的有效性。
In view of the actual distribution and transportation,the optimization of the path is not only to meet the shortestpath,but also to meet the shortest time and the lowest cost. On the basis of the ant algorithm,this paper proposes a path calculationmethod of correlation coefficient and local optimal improvement and AtuoCAD is used to improve the ant algorithm,through the example of verification,the results show that the effectiveness of this algorithm.
In view of the actual distribution and transportation,the optimization of the path is not only to meet the shortestpath,but also to meet the shortest time and the lowest cost. On the basis of the ant algorithm,this paper proposes a path calculationmethod of correlation coefficient and local optimal improvement and AtuoCAD is used to improve the ant algorithm,through the example of verification,the results show that the effectiveness of this algorithm.
引文
[1]张勇.基于改进蚁群算法物流配送路径优化的研究[J].控制工程,2015,22(2):252-256.ZHANG Yong. Research on Optimization of Logistics Distribution Routing Based on Improved Ant Colony Algorithm[J]. Control Engineering,2015,22(2):252-256.
[2]王玉富.基于聚类蚁群算法的多车辆路径优化系统的实现[J].湖北民族学院学报(自然科学版),2015(2):200-204.WANG Yufu. Realization of multi-vehicle path optimization system based on clustering ant colony algorithm[J].Journal of Hubei University for Nationalities(Natural Science Edition),2015(2):200-204.
[3]符志强,刘磊安.基于蚁群算法的物流配送优化系统设计[J].现代计算机(专业版),2014(6):22-24.FU Zhiqiang,LIU Lei'an. Design of Logistics DistributionOptimization System Based on Ant Colony Algorithm[J].Modern Computer(Professional),2014(6):22-24.
[4]陈世欢,李毅.基于改进蚁群算法的改航路径规划[J].计算机技术与发展,2015(2):52-54.CHEN Shihuan,LI Yi. Reconstruction route based on improved ant colony algorithm[J]. Computer Technology andDevelopment,2015(2):52-54.
[5]陈迎欣.基于改进蚁群算法的车辆路径优化问题研究[J].计算机应用研究,2012,29(6):2031-2034.CHEN Yingxin. Research on Vehicle Routing ProblemBased on Improved Ant Colony Algorithm[J]. ComputerApplication Research,2012,29(6):2031-2034.
[6]吴云志,乐毅,王超,等.蚁群算法在物流路径优化中的应用及仿真[J].合肥工业大学学报(自然科学版),2009,32(2):211-214.WU Yunzhi,YUE Yi,WANG Chao,et al. Application andsimulation of ant colony algorithm in logistics path optimization[J]Journal of Hefei University of Technology(Natural Science Edition),2009,32(2):211-214.
[7]刘志硕,申金升,柴跃廷.基于自适应蚁群算法的车辆路径问题研究[J].控制与决策,2005,20(5):562-566.LIU Zhishuo,SHEN Jinsheng,CHAI Yueting. Adaptiveant colony algorithm for vehicle routing problem of[J].control and decision based on,2005,20(5):562-566.
[8]裴振兵,陈雪波.改进蚁群算法及在车辆运输调度中的应用[J].信息与控制,2015,44(6):753-758.PEI Zhenbing,CHEN Xuebo. Improved ant colony algorithm and its application in vehicle transportation scheduling[J]. Information and control,2015,44(6):753-758.
[9]Colorni A,Dorigo M,Maniezzo V. Distributed optimizationby ant colonies[C]//Proceedings of the First EuropeanCon-ference on Artificial Life,1991:134-142.
[10] Dorigo M,Gambardella L M. Ant colony system:acoop-erative learning approach to the traveling salesmanprob-lem[J]. IEEE Transactions on Evolutionary Computation,1997,1(1):53-66.
[11] Gambardella L M,Dorigo M. Ant-Q:a reinforcementlearning approach to the traveling salesman problem[C]//Proceedingsof the Twelfth International Conference onMachine Learning,1995:252-260.
[12]吴洁明.物流配送车辆路径优化问题的仿真研究[J].计算机仿真,2011,07:5-8.WU Jieming. Simulation study on vehicle routing problem of logistics distribution[J]. Computer simulation,2011,07:5-8.
[13]肖力.物流配送车辆路径优化问题的仿真研究[J].鄂州大学学报,2012,02:5-8.XIAO Li. Simulation study on vehicle routing problem oflogistics distribution[J]. Journal of Ezhou University,2012,02:5-8.
[14]乔文山.城市物流配送车辆优化调度的仿真研究[D].南京:南京林业大学,2010.QIAO Wenshan. Simulation study on optimal schedulingof urban logistics distribution vehicles[D]. Nanjing:Nanjing Forestry University,2010.
[15]邓灵斌,邵军.蚁群算法在自动化仓库路径规划中的应用[J].情报探索,2014(12):70-72,132.DENG Lingbin,SHAO Jun. ant colony algorithm for automated warehouse Path Planning[J]. Information exploration,2014(12):70-72132
[16]马建华,房勇,袁杰.多车场多车型最快完成车辆路径问题的变异蚁群算法[J].系统工程理论与实践,2011,31(8):1508-1516.MA Jianhua,FANG Yong,YUAN Jie. Variation of antcolony algorithm for vehicle routing problem with multidepot and multi vehicle model[J]. System engineeringtheory and practice,2011,31(8):1508-1516.
[17]李琳,刘士新,唐加福.改进的蚁群算法求解带时间窗的车辆路径问题[J].控制与决策,2010,25(9):1379-1383.LI Lin,LIU Shixin,TANG Jiafu.[J]. improved ant colony algorithm for vehicle routing problem with time window for the control and decision,2010,25(9):1379-1383.
[2]王玉富.基于聚类蚁群算法的多车辆路径优化系统的实现[J].湖北民族学院学报(自然科学版),2015(2):200-204.WANG Yufu. Realization of multi-vehicle path optimization system based on clustering ant colony algorithm[J].Journal of Hubei University for Nationalities(Natural Science Edition),2015(2):200-204.
[3]符志强,刘磊安.基于蚁群算法的物流配送优化系统设计[J].现代计算机(专业版),2014(6):22-24.FU Zhiqiang,LIU Lei'an. Design of Logistics DistributionOptimization System Based on Ant Colony Algorithm[J].Modern Computer(Professional),2014(6):22-24.
[4]陈世欢,李毅.基于改进蚁群算法的改航路径规划[J].计算机技术与发展,2015(2):52-54.CHEN Shihuan,LI Yi. Reconstruction route based on improved ant colony algorithm[J]. Computer Technology andDevelopment,2015(2):52-54.
[5]陈迎欣.基于改进蚁群算法的车辆路径优化问题研究[J].计算机应用研究,2012,29(6):2031-2034.CHEN Yingxin. Research on Vehicle Routing ProblemBased on Improved Ant Colony Algorithm[J]. ComputerApplication Research,2012,29(6):2031-2034.
[6]吴云志,乐毅,王超,等.蚁群算法在物流路径优化中的应用及仿真[J].合肥工业大学学报(自然科学版),2009,32(2):211-214.WU Yunzhi,YUE Yi,WANG Chao,et al. Application andsimulation of ant colony algorithm in logistics path optimization[J]Journal of Hefei University of Technology(Natural Science Edition),2009,32(2):211-214.
[7]刘志硕,申金升,柴跃廷.基于自适应蚁群算法的车辆路径问题研究[J].控制与决策,2005,20(5):562-566.LIU Zhishuo,SHEN Jinsheng,CHAI Yueting. Adaptiveant colony algorithm for vehicle routing problem of[J].control and decision based on,2005,20(5):562-566.
[8]裴振兵,陈雪波.改进蚁群算法及在车辆运输调度中的应用[J].信息与控制,2015,44(6):753-758.PEI Zhenbing,CHEN Xuebo. Improved ant colony algorithm and its application in vehicle transportation scheduling[J]. Information and control,2015,44(6):753-758.
[9]Colorni A,Dorigo M,Maniezzo V. Distributed optimizationby ant colonies[C]//Proceedings of the First EuropeanCon-ference on Artificial Life,1991:134-142.
[10] Dorigo M,Gambardella L M. Ant colony system:acoop-erative learning approach to the traveling salesmanprob-lem[J]. IEEE Transactions on Evolutionary Computation,1997,1(1):53-66.
[11] Gambardella L M,Dorigo M. Ant-Q:a reinforcementlearning approach to the traveling salesman problem[C]//Proceedingsof the Twelfth International Conference onMachine Learning,1995:252-260.
[12]吴洁明.物流配送车辆路径优化问题的仿真研究[J].计算机仿真,2011,07:5-8.WU Jieming. Simulation study on vehicle routing problem of logistics distribution[J]. Computer simulation,2011,07:5-8.
[13]肖力.物流配送车辆路径优化问题的仿真研究[J].鄂州大学学报,2012,02:5-8.XIAO Li. Simulation study on vehicle routing problem oflogistics distribution[J]. Journal of Ezhou University,2012,02:5-8.
[14]乔文山.城市物流配送车辆优化调度的仿真研究[D].南京:南京林业大学,2010.QIAO Wenshan. Simulation study on optimal schedulingof urban logistics distribution vehicles[D]. Nanjing:Nanjing Forestry University,2010.
[15]邓灵斌,邵军.蚁群算法在自动化仓库路径规划中的应用[J].情报探索,2014(12):70-72,132.DENG Lingbin,SHAO Jun. ant colony algorithm for automated warehouse Path Planning[J]. Information exploration,2014(12):70-72132
[16]马建华,房勇,袁杰.多车场多车型最快完成车辆路径问题的变异蚁群算法[J].系统工程理论与实践,2011,31(8):1508-1516.MA Jianhua,FANG Yong,YUAN Jie. Variation of antcolony algorithm for vehicle routing problem with multidepot and multi vehicle model[J]. System engineeringtheory and practice,2011,31(8):1508-1516.
[17]李琳,刘士新,唐加福.改进的蚁群算法求解带时间窗的车辆路径问题[J].控制与决策,2010,25(9):1379-1383.LI Lin,LIU Shixin,TANG Jiafu.[J]. improved ant colony algorithm for vehicle routing problem with time window for the control and decision,2010,25(9):1379-1383.