基于聚类—遗传混合算法的物流配送路径优化研究
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摘要
随着经济和社会的迅猛发展,物流也更需要科学化、合理化、全球化、信息化、网络化以及智能化,从而更好的为企业创造出更大的利润,进而成为企业的“第三利润源泉”；然而,在物流活动中,配送属于“最终配置”,是直接与最终消费者相连的环节；另外,在物流成本中,配送成本占了相当高的比重；因此,如何有效地、合理地、恰当地、准确地安排物流配送路径,对配送的成本、效率、效益、速度影响都很大；要使物流配送路径更好的优化,必须应用科学的、合理的、高效的方法,这是现代物流配送中的一项十分重要的活动。
近几年来,在物流配送活动中,确定物流配送路径的问题是配送路径优化问题的重点研究领域和应用领域；然而,由于其计算的复杂性,几乎所有的物流配送路径优化问题都属于NP(非多项式算法)难题,目前,还尚未有高效的、精确的算法存在；本文将聚类分析技术和遗传算法进行结合,并运用于物流配送路径优化问题中,提出了解决物流配送路径优化问题的基于聚类-遗传混合算法。
随着启发式算法的日渐成熟,很多专家和学者们通过改进的启发式算法对实际问题进行求解。本文正是通过改进遗传算法的编码规则,克服了传统二进制编码规则的冗长性；另外,本文设计了一个随机开关,控制遗传算法的变异操作,避免了遗传算法局部最优化的发生。通过聚类分析技术,将配送的客户进行综合优先级聚类,最后通过配送路径优化的数学模型,提出了基于聚类-遗传混合算法的配送路径优化的数学模型。由于研究时间和研究水平有限,本文也存在很多不足之处,还待以后的研究进行进一步完善。
图8表7参75
With the continuous economic and social development, logistics need more scientific and reasonable, globalization, information technology, networking and intelligent, in order to create greater profits for the enterprise, it has become "the third profit source." The distribution of logistics activities which is directly connected to the final consumer is in the "final configuration". All the costs in the logistics activities, distribution costs account for a very high proportion. How to create more effective, reasonable, appropriate and accurate logistics which can better distribution arrangements for the path influences the costs, efficiency, effectiveness, speed of the distribution. Applying scientific, rational and efficient approach to optimize the logistics distribution routing problem is of great importance in a modern logistics and distribution activities.
What's more, how to decide distribution routing problem in Logistics and distribution activities plays an important role in recent study of distribution routing problem research and applications. However, because of its computational complexity, almost the entire logistics distribution routing problem belongs to NP problems, efficient and accurate algorithm is unlikely to exist. Moreover, this paper will combine cluster analysis and genetic algorithm and apply to vehicle routing problem in logistics distribution. Accordingly, based on clustering and Genetic Algorithm, we will propose clustering-Genetic Algorithm to solve the problem of optimization of distribution routing problem.
With the maturing of heuristic algorithms, many experts and scholars has proposed the improved heuristic algorithm to solve practical problems of vehicle routing problem. In order to overcome the Shortcomings of traditional binary encoding rules, this article alter the coding rules of genetic algorithm, that is, natural number coding rules. In addition, the paper has designed a randomized switch to control the mutation operation of genetic algorithm for the sake of avoiding the occurrence of local optimization. With regard to the clustering analysis technology, we have classified the customer of the distribution center by the integrated priority clustering. Finally, by bettering the distribution route optimization model, this paper has proposed the mathematical model based on clustering-Genetic Algorithm to optimize the vehicle routing problem. Because of the limitation of time, what I have studied has many deficiencies. In a word, more research work should be put on in near future.
Figure 8 Table 7 References 75
近几年来,在物流配送活动中,确定物流配送路径的问题是配送路径优化问题的重点研究领域和应用领域；然而,由于其计算的复杂性,几乎所有的物流配送路径优化问题都属于NP(非多项式算法)难题,目前,还尚未有高效的、精确的算法存在；本文将聚类分析技术和遗传算法进行结合,并运用于物流配送路径优化问题中,提出了解决物流配送路径优化问题的基于聚类-遗传混合算法。
随着启发式算法的日渐成熟,很多专家和学者们通过改进的启发式算法对实际问题进行求解。本文正是通过改进遗传算法的编码规则,克服了传统二进制编码规则的冗长性；另外,本文设计了一个随机开关,控制遗传算法的变异操作,避免了遗传算法局部最优化的发生。通过聚类分析技术,将配送的客户进行综合优先级聚类,最后通过配送路径优化的数学模型,提出了基于聚类-遗传混合算法的配送路径优化的数学模型。由于研究时间和研究水平有限,本文也存在很多不足之处,还待以后的研究进行进一步完善。
图8表7参75
With the continuous economic and social development, logistics need more scientific and reasonable, globalization, information technology, networking and intelligent, in order to create greater profits for the enterprise, it has become "the third profit source." The distribution of logistics activities which is directly connected to the final consumer is in the "final configuration". All the costs in the logistics activities, distribution costs account for a very high proportion. How to create more effective, reasonable, appropriate and accurate logistics which can better distribution arrangements for the path influences the costs, efficiency, effectiveness, speed of the distribution. Applying scientific, rational and efficient approach to optimize the logistics distribution routing problem is of great importance in a modern logistics and distribution activities.
What's more, how to decide distribution routing problem in Logistics and distribution activities plays an important role in recent study of distribution routing problem research and applications. However, because of its computational complexity, almost the entire logistics distribution routing problem belongs to NP problems, efficient and accurate algorithm is unlikely to exist. Moreover, this paper will combine cluster analysis and genetic algorithm and apply to vehicle routing problem in logistics distribution. Accordingly, based on clustering and Genetic Algorithm, we will propose clustering-Genetic Algorithm to solve the problem of optimization of distribution routing problem.
With the maturing of heuristic algorithms, many experts and scholars has proposed the improved heuristic algorithm to solve practical problems of vehicle routing problem. In order to overcome the Shortcomings of traditional binary encoding rules, this article alter the coding rules of genetic algorithm, that is, natural number coding rules. In addition, the paper has designed a randomized switch to control the mutation operation of genetic algorithm for the sake of avoiding the occurrence of local optimization. With regard to the clustering analysis technology, we have classified the customer of the distribution center by the integrated priority clustering. Finally, by bettering the distribution route optimization model, this paper has proposed the mathematical model based on clustering-Genetic Algorithm to optimize the vehicle routing problem. Because of the limitation of time, what I have studied has many deficiencies. In a word, more research work should be put on in near future.
Figure 8 Table 7 References 75
引文
[1]郎茂祥.配送车辆优化调度模型与算法[M].北京：电子工业出版社,2009:1-7
[2]刘亚非.连锁店的物流配送路径选择问题研究.中南大学硕士学位论文,2004：11-12
[3]符卓,陈斯卫.车辆路径问题的研究现状与发展趋势.中国运筹学会第七届学术交流会论文集,2004：997-1002
[4]Dantzig GB, Ramser J.H. The truck dispatching problem [J]. Management Science,1959, 6:80
[5]张丹羽.现代物流配送中心车辆线路优化方案研究与应用.山东大学硕士学位论文,2005,15-25
[6]Clarke G., Wright J. V. Scheduling of vehicles from a central depot to a number of delivery points [J]. Operations Research,1964,12:268-581
[7]Baker B.M., Ayechew M.A. A genetic algorithm for the vehicle routing problem [J]. Computers and Operations Research,2003,30 (5):787-801
[8]Wassan N. A., Osman H. Tabu search variants for the mix fleet vehicle routing problem [J]. Journal of the Operational Research Society,2002,53:768-782
[9]Cordesu F., Laporte G. et al. A unified tabu search heuristic for vehicle routing problems with time windows [J] Journal of the Operational Research Society,2001,52 (8):928-936
[10]Tailland, Gendreau M et al. A tabu search heuristic for the vehicle routing problem with soft time windows [J],Transportation Science,1997,31 (2):170-186
[11]Michel Gendreau, Alain Hertz, and Gilbert Laporte. A Tabu Heuristic for the Vehicle Routing Problem [J] Management Science,1994,40(10):1276-1290
[12]Barbarosoglu G., Ozgur D. A Tabu Search Algorithm for The vehicle Routing Problem [J]. Computers & Operations Research,1999,26:255-270
[13]C.T. Su, H.H. Chen. Vehicle Routing Design of Physical Distribution Center [J] Journal of the Chinese Institute of Industrial Engineers,1999,16(3):410-417
[14]庞凌.基于蚁群算法的城市物流配送路径优化[J].物流工程与管理,2010,32(8)：146-149
[15]王红玲,郑纲等.基于改进粒子群算法的生鲜农产品配送路径优化研究[J].安徽农业科学,2010,38(31)：17961-17962
[16]潘超杰.基于BP人工神经网络的物流配送中心选址决策[J].知识经济,2010,9：10-11
[17]袁庆达,杜文等.带软时间窗的混合车队车辆路线问题的模型和算法研究[J].西南交通大学学报,2001,36(4)：401-406
[18]宾松,符卓.求解带时间窗的车辆路径问题的改进遗传算法[J].系统工程,2003,21(6)：12-15
[19]Duhamel C, Rousseau M et al. A tabu search heuristic for the vehicle routing problem with back hauls and time windows [J] Transportation Science,1997,31:49-59
[20]Salhi S, Nagy G. A cluster insertion heuristic for single and multiple depot vehicle routing problems with back hauling [J] Journal of the Operational Research Society,1999,50: 1034-1042
[21]Dumas Y, Desrosiers J et al. The pickup and delivery problem with time windows [J] European Journal of Operational Research,1991,54:7-22
[22]Fisher M, Tang B et al. A network flow based heuristic for bulk pickup and delivery routing [J]. Transportation Science,1995,29 (1):45-55
[23]Dethlof J. Relation between vehicle routing problems:an insertion heuristic for the vehicle routing problem with simultaneous delivery and pick-up applied to the vehicle routing problem with Back hauls [J]. Journal of the Operational Research Society,2002,53:115-118
[24]Lenstra JK, Rinnooy K. Complexity of vehicle routing and scheduling problem [J] Networks, 1981,11:221-227
[25]Savelsbergh MWP. Local search in routing problems with time windows [J] Operations Research,1985,33 (4):285-305
[26]Solomon MM. On the worst-case performance of some heuristics for the vehicle routing and scheduling problem with time window constraints Networks,1986, (16):161-174
[27]谢秉磊,李良等.求解旅行商问题的模拟退火算法[J].系统工程理论方法应用,2002,11(3)：20-23
[28]李松,刘兴等.基于混合禁忌搜索算法的物流配送路径优化问题研究[J].现代物流,2010,29(3)：67-69
[29]陈艳艳,宋健民.基于地理信息系统及遗传算法的道路规划[J].计算机工程与应用,2002,3：21-22
[30]董宗然,周慧禁忌搜索算法评述软件工程师,2010 Z1 96-98
[31]贾向权模拟退火算法在装箱问题中的应用电脑知识与技术20105 1179-1181
[32]孙改平郭海文信息素动态更新的改进蚁群算法福建电脑2010 1 81-82
[33]郎茂祥.配送车辆优化调度模型与算法[M].北京：电子工业出版社,2009：23-28
[34]郎茂祥.基于遗传算法的物流配送路径优化问题研究[J].中国公路学报,2002,15(3)：76-78
[35]张潜,李钟慎等.基于模糊优化的物流配送路径(MLRP)问题研究[J].控制与决策,2006,21(6)：689-692
[36]袁庆达 闫昱Tabu Search算法在优化配送路线问题中的应用计算机工程2001 1186-89
[37]王庆,闫丽君.电子商务环境下物流配送路径优化研究[J].天津商业大学学报,2010,30(3)：27-30
[38]许星.物流配送路径优化问题研究.浙江大学硕士学位论文.2006：15-19
[39]周程.物流配送路径优化策略研究[J].武汉理工大学学报(交通科学与工程版),2005,29(5)：797-800
[40]赵建民,刘芳华等.有时间窗物流配送路径优化问题的混合并购算法[J].浙江师范大学学报,2010,33(2)：122-127
[41]东方.基于免疫算法的物流配送VRP研究.大连海事大学硕士学位论文,2006：11-15
[42]张远福.VRP和制造网络流算法的研究.山东科技大学硕士学位论文,2000：9-13
[43]李娜.VRP在支线船舶调度中的扩展应用研究.大连海事大学硕士学位论文,2006：6-10
[44]盛倩蓉.基于改进遗传算法的车辆路径问题研究.武汉理工大学硕士学位论文,2006：10-13
[45]鲍正益.模糊聚类算法及其有效性研究.厦门大学硕士学位论文,2006：23-34
[46]张洪刚,刘刚.FCM聚类算法的研究[J].自动化学报,2002,28(4)：631-636
[47]杨占华.聚类分析研究及其在文本挖掘中的应用.西南交通大学硕士学位论文,2006：4-9
[48]罗贤缙.聚类分析在电力营销中的应用研究.华北电力大学硕士学位论文,2004：15-18
[49]李浪波.聚类分析在科学数据挖掘中的应用研究.电子科技大学硕士学位论文,2006：23-35
[50]刘晓霞.聚类分析在客户细分领域的应用研究.西北大学硕士学位论文,2006：45-51
[51]王鑫.数据挖掘中聚类分析算法的研究.山东师范大学硕士学位论文,2006：32-36
[52]戴涛.聚类分析算法研究.清华大学硕士学位论文,2004：26-36
[53]薛明轩.基于聚类分析的医疗保险系统.长春理工大学硕士学位论文,2004：21-28
[54]张莉,周伟达.核聚类算法[J].计算机学报,2002,25(6)：587-590
[55]胡玉锁,陈宗海.基于混合遗传算法的聚类分析[J].模式识别与人工智能,2001,14(3)：352-355.
[56]史忠植.知识发现[M].北京：清华大学出版社,2002：116-142
[57]韩波.遗传算法在地质雷达成像中的应用研究.中国海洋大学硕士学位论文,2005：16-22
[58]陈城辉,徐永能等.遗传算法在多车型军备物资配送路径优化中的应用[J].四川兵工学报,2010,31(2)：13-15
[59]赵蕾.遗传算法在通信网优化中的实现.山东大学硕士学位论文,2005：11-15
[60]徐鹏,沈金星.基子改进遗传算法的配送路径优但方案[J].科教论丛,2010：216-218
[61]汤岩.遗传算法在装箱问题中的应用.大连海事大学硕士学位论文,2005：17-20
[62]郭淑红,杨晓慧.遗传算法在物流配送路径优化问题中的应用[J].信息科学,2009：123-125
[63]张潜,高立群.物流配送路径多目标优化的聚类-改进遗传算法[J].控制与决策,2003,18(4)：418-422
[64]朱树人,李文彬等.一种带软时间窗的物流配送路径优化遗传算法[J].计算机工程与科学,2005,27(12)：108-110
[65]王忠勇.优化的遗传算法及其在货物配送问题中的应用[J].福建电脑,2008,01：73-80
[66]郭淑红,杨晓慧.遗传算法在物流配送路径优化问题中的应用[J].硅谷,2009,01：46
[67]花本高,丛雪.基于遗传算法物流配送路线优化研究与实现[J].电脑知识与技术,2010,24：6834-6839
[68]杨运峰,靳小红等.改进的遗传算法在物流配送中的应用[J].商场现代化,2008,08：152
[69]庞留勇,张秀全.物流配送车辆调度问题的改进遗传算法[J].天中学刊,2008,02：57-59
[70]陈大立,薛东彬等.用遗传算法解决货运物流配送问题[J].科技咨询导报,2007,18：156
[71]李海,于文莉等.启发式遗传算法在电子商务下物流配送中心选址中的研究[J].商场现代化,2007,36：138-139
[72]张威,罗大庸.遗传算法在物流车辆配送中的应用[J].科技资讯,2007,35：183-184
[73]郎茂祥,胡思继.用混合遗传算法求解物流配送路径优化问题的研究[J].中国管理科学,2002,05：51-56
[74]王素云,李军.基于遗传算法的物流配送车辆优化调度[J].商场现代化,2006,28：119-120
[75]吕楠,刘中.遗传算法在精益物流配送线路优化中的应用[J].山东交通科技,2006,01：91-93
[2]刘亚非.连锁店的物流配送路径选择问题研究.中南大学硕士学位论文,2004：11-12
[3]符卓,陈斯卫.车辆路径问题的研究现状与发展趋势.中国运筹学会第七届学术交流会论文集,2004：997-1002
[4]Dantzig GB, Ramser J.H. The truck dispatching problem [J]. Management Science,1959, 6:80
[5]张丹羽.现代物流配送中心车辆线路优化方案研究与应用.山东大学硕士学位论文,2005,15-25
[6]Clarke G., Wright J. V. Scheduling of vehicles from a central depot to a number of delivery points [J]. Operations Research,1964,12:268-581
[7]Baker B.M., Ayechew M.A. A genetic algorithm for the vehicle routing problem [J]. Computers and Operations Research,2003,30 (5):787-801
[8]Wassan N. A., Osman H. Tabu search variants for the mix fleet vehicle routing problem [J]. Journal of the Operational Research Society,2002,53:768-782
[9]Cordesu F., Laporte G. et al. A unified tabu search heuristic for vehicle routing problems with time windows [J] Journal of the Operational Research Society,2001,52 (8):928-936
[10]Tailland, Gendreau M et al. A tabu search heuristic for the vehicle routing problem with soft time windows [J],Transportation Science,1997,31 (2):170-186
[11]Michel Gendreau, Alain Hertz, and Gilbert Laporte. A Tabu Heuristic for the Vehicle Routing Problem [J] Management Science,1994,40(10):1276-1290
[12]Barbarosoglu G., Ozgur D. A Tabu Search Algorithm for The vehicle Routing Problem [J]. Computers & Operations Research,1999,26:255-270
[13]C.T. Su, H.H. Chen. Vehicle Routing Design of Physical Distribution Center [J] Journal of the Chinese Institute of Industrial Engineers,1999,16(3):410-417
[14]庞凌.基于蚁群算法的城市物流配送路径优化[J].物流工程与管理,2010,32(8)：146-149
[15]王红玲,郑纲等.基于改进粒子群算法的生鲜农产品配送路径优化研究[J].安徽农业科学,2010,38(31)：17961-17962
[16]潘超杰.基于BP人工神经网络的物流配送中心选址决策[J].知识经济,2010,9：10-11
[17]袁庆达,杜文等.带软时间窗的混合车队车辆路线问题的模型和算法研究[J].西南交通大学学报,2001,36(4)：401-406
[18]宾松,符卓.求解带时间窗的车辆路径问题的改进遗传算法[J].系统工程,2003,21(6)：12-15
[19]Duhamel C, Rousseau M et al. A tabu search heuristic for the vehicle routing problem with back hauls and time windows [J] Transportation Science,1997,31:49-59
[20]Salhi S, Nagy G. A cluster insertion heuristic for single and multiple depot vehicle routing problems with back hauling [J] Journal of the Operational Research Society,1999,50: 1034-1042
[21]Dumas Y, Desrosiers J et al. The pickup and delivery problem with time windows [J] European Journal of Operational Research,1991,54:7-22
[22]Fisher M, Tang B et al. A network flow based heuristic for bulk pickup and delivery routing [J]. Transportation Science,1995,29 (1):45-55
[23]Dethlof J. Relation between vehicle routing problems:an insertion heuristic for the vehicle routing problem with simultaneous delivery and pick-up applied to the vehicle routing problem with Back hauls [J]. Journal of the Operational Research Society,2002,53:115-118
[24]Lenstra JK, Rinnooy K. Complexity of vehicle routing and scheduling problem [J] Networks, 1981,11:221-227
[25]Savelsbergh MWP. Local search in routing problems with time windows [J] Operations Research,1985,33 (4):285-305
[26]Solomon MM. On the worst-case performance of some heuristics for the vehicle routing and scheduling problem with time window constraints Networks,1986, (16):161-174
[27]谢秉磊,李良等.求解旅行商问题的模拟退火算法[J].系统工程理论方法应用,2002,11(3)：20-23
[28]李松,刘兴等.基于混合禁忌搜索算法的物流配送路径优化问题研究[J].现代物流,2010,29(3)：67-69
[29]陈艳艳,宋健民.基于地理信息系统及遗传算法的道路规划[J].计算机工程与应用,2002,3：21-22
[30]董宗然,周慧禁忌搜索算法评述软件工程师,2010 Z1 96-98
[31]贾向权模拟退火算法在装箱问题中的应用电脑知识与技术20105 1179-1181
[32]孙改平郭海文信息素动态更新的改进蚁群算法福建电脑2010 1 81-82
[33]郎茂祥.配送车辆优化调度模型与算法[M].北京：电子工业出版社,2009：23-28
[34]郎茂祥.基于遗传算法的物流配送路径优化问题研究[J].中国公路学报,2002,15(3)：76-78
[35]张潜,李钟慎等.基于模糊优化的物流配送路径(MLRP)问题研究[J].控制与决策,2006,21(6)：689-692
[36]袁庆达 闫昱Tabu Search算法在优化配送路线问题中的应用计算机工程2001 1186-89
[37]王庆,闫丽君.电子商务环境下物流配送路径优化研究[J].天津商业大学学报,2010,30(3)：27-30
[38]许星.物流配送路径优化问题研究.浙江大学硕士学位论文.2006：15-19
[39]周程.物流配送路径优化策略研究[J].武汉理工大学学报(交通科学与工程版),2005,29(5)：797-800
[40]赵建民,刘芳华等.有时间窗物流配送路径优化问题的混合并购算法[J].浙江师范大学学报,2010,33(2)：122-127
[41]东方.基于免疫算法的物流配送VRP研究.大连海事大学硕士学位论文,2006：11-15
[42]张远福.VRP和制造网络流算法的研究.山东科技大学硕士学位论文,2000：9-13
[43]李娜.VRP在支线船舶调度中的扩展应用研究.大连海事大学硕士学位论文,2006：6-10
[44]盛倩蓉.基于改进遗传算法的车辆路径问题研究.武汉理工大学硕士学位论文,2006：10-13
[45]鲍正益.模糊聚类算法及其有效性研究.厦门大学硕士学位论文,2006：23-34
[46]张洪刚,刘刚.FCM聚类算法的研究[J].自动化学报,2002,28(4)：631-636
[47]杨占华.聚类分析研究及其在文本挖掘中的应用.西南交通大学硕士学位论文,2006：4-9
[48]罗贤缙.聚类分析在电力营销中的应用研究.华北电力大学硕士学位论文,2004：15-18
[49]李浪波.聚类分析在科学数据挖掘中的应用研究.电子科技大学硕士学位论文,2006：23-35
[50]刘晓霞.聚类分析在客户细分领域的应用研究.西北大学硕士学位论文,2006：45-51
[51]王鑫.数据挖掘中聚类分析算法的研究.山东师范大学硕士学位论文,2006：32-36
[52]戴涛.聚类分析算法研究.清华大学硕士学位论文,2004：26-36
[53]薛明轩.基于聚类分析的医疗保险系统.长春理工大学硕士学位论文,2004：21-28
[54]张莉,周伟达.核聚类算法[J].计算机学报,2002,25(6)：587-590
[55]胡玉锁,陈宗海.基于混合遗传算法的聚类分析[J].模式识别与人工智能,2001,14(3)：352-355.
[56]史忠植.知识发现[M].北京：清华大学出版社,2002：116-142
[57]韩波.遗传算法在地质雷达成像中的应用研究.中国海洋大学硕士学位论文,2005：16-22
[58]陈城辉,徐永能等.遗传算法在多车型军备物资配送路径优化中的应用[J].四川兵工学报,2010,31(2)：13-15
[59]赵蕾.遗传算法在通信网优化中的实现.山东大学硕士学位论文,2005：11-15
[60]徐鹏,沈金星.基子改进遗传算法的配送路径优但方案[J].科教论丛,2010：216-218
[61]汤岩.遗传算法在装箱问题中的应用.大连海事大学硕士学位论文,2005：17-20
[62]郭淑红,杨晓慧.遗传算法在物流配送路径优化问题中的应用[J].信息科学,2009：123-125
[63]张潜,高立群.物流配送路径多目标优化的聚类-改进遗传算法[J].控制与决策,2003,18(4)：418-422
[64]朱树人,李文彬等.一种带软时间窗的物流配送路径优化遗传算法[J].计算机工程与科学,2005,27(12)：108-110
[65]王忠勇.优化的遗传算法及其在货物配送问题中的应用[J].福建电脑,2008,01：73-80
[66]郭淑红,杨晓慧.遗传算法在物流配送路径优化问题中的应用[J].硅谷,2009,01：46
[67]花本高,丛雪.基于遗传算法物流配送路线优化研究与实现[J].电脑知识与技术,2010,24：6834-6839
[68]杨运峰,靳小红等.改进的遗传算法在物流配送中的应用[J].商场现代化,2008,08：152
[69]庞留勇,张秀全.物流配送车辆调度问题的改进遗传算法[J].天中学刊,2008,02：57-59
[70]陈大立,薛东彬等.用遗传算法解决货运物流配送问题[J].科技咨询导报,2007,18：156
[71]李海,于文莉等.启发式遗传算法在电子商务下物流配送中心选址中的研究[J].商场现代化,2007,36：138-139
[72]张威,罗大庸.遗传算法在物流车辆配送中的应用[J].科技资讯,2007,35：183-184
[73]郎茂祥,胡思继.用混合遗传算法求解物流配送路径优化问题的研究[J].中国管理科学,2002,05：51-56
[74]王素云,李军.基于遗传算法的物流配送车辆优化调度[J].商场现代化,2006,28：119-120
[75]吕楠,刘中.遗传算法在精益物流配送线路优化中的应用[J].山东交通科技,2006,01：91-93