连锁企业物流配送中心配送技术的研究
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摘要
本文首先对连锁经营的基本特征及目标，配送中心的定义，配送中心的运作过程及各部分的功能作了概括性的描述。接着对与配送中心有关的部分优化技术—双拣选台水平旋转货架拣选路径的优化、固定货架拣选路径的优化、车辆运输线路的优化作了详细阐述。
分层旋转货架与固定货架是自动化仓库的存储设备。对其拣选路径进行优化能大大提高自动化仓库的作业效率。旋转货架是自动化仓库的重要组成部分，特别适合小件物品的存放。已有的文献大多集中于单拣选台拣选路径优化问题，对于双拣选台多层旋转货架的拣选路径问题则研究的很少。本文提出一种启发式与遗传算法相结合的算法，对两级遗传算法进行了改进。仿真结果表明该算法能有效降低每层货架的反向次数，降低了拣选作业时间。
固定货架在自动化仓库中占了很大的比重，许多物品仍存放在固定货架区，特别是体积较大的物品。随着自动化程度的提高及拣选规模的扩大，需要对大规模拣选任务的拣选路径进行优化，本文针对大规模拣选任务时固定货架的拣选路径优化，提出一种分解—合成的方法：根据货物在货架中的位置分为几部分，用遗传算法得到组内的满意解，再用启发式算法将各部分连成一条回路，得到最后的满意解。实验结果表明，与简单遗传算法相比，该算法的性能及优化率都得到了极大的提高。
配送运输是配送中心送货出门的最后一道程序，因此配送效率的高低直接影响配送的质量。对其行驶路线路进行优化将极大地降低运输成本，提高运输效率。本文对不同数量运输任务的车辆行驶线路进行了优化。在初始种群的产生时，采用聚类的方法，从实验结果可以出，与简单的遗传算法相比，对不同数量的运输任务，该算法的优化率有不同程度的提高。
In this dissertation, several aspects of chain store running and logistics distribution center such as the concept, the features, the functions and the operation process are introduced at first. Some scheduling optimization problems of logistics distribution center such as order-picking for multi-level carousel with two server order-picking for fixed shelves and vehicle scheduling for distribution traffic are indicated.
The order-picking route optimization for carousel and fixed shelves can largely improve the efficiency of the automated warehouse. The multi-level carousel is the latest development in the automated warehouse. It is specifically applied to store small parts. The literatures on order-picking problem of the carousel were mainly concentrated on the single server, few papers were devoted to the case of two servers. In this paper, based on two-level genetic algorithm, an improved approach is proposed to order-picking optimization of multi-level carousel system with two servers. The heuristic method was first used in single carousel optimization, and then genetic algorithm was used in entirety optimization. The results of the computer simulation show that it can deeply shorten the time of sorting out.
Fixed shelves have large proportion in cubic warehouse and many goods store in it especially large goods. A new approach is proposed in this paper for extensive order-picking optimization of fixed shelves system. The whole indenture is firstly separated into some sub-indenture, and genetic algorithm was used to optimize every sub-indenture, then heuristic method was used to connect optimized sub-indenture. The results of numerical simulations show the validity of this approach.
Distribution traffic is the last program for distribution center sending the goods out. The efficiency of traffic will affect the quality of distribution. The route optimization for traffic can reduce traffic cost and advance traffic efficiency. For this purpose, an improved genetic algorithm is given to optimize the distribution route for different traffic task. The numerical
results of different size show the validity of improved algorithm comparing with simple genetic algorithm.
分层旋转货架与固定货架是自动化仓库的存储设备。对其拣选路径进行优化能大大提高自动化仓库的作业效率。旋转货架是自动化仓库的重要组成部分，特别适合小件物品的存放。已有的文献大多集中于单拣选台拣选路径优化问题，对于双拣选台多层旋转货架的拣选路径问题则研究的很少。本文提出一种启发式与遗传算法相结合的算法，对两级遗传算法进行了改进。仿真结果表明该算法能有效降低每层货架的反向次数，降低了拣选作业时间。
固定货架在自动化仓库中占了很大的比重，许多物品仍存放在固定货架区，特别是体积较大的物品。随着自动化程度的提高及拣选规模的扩大，需要对大规模拣选任务的拣选路径进行优化，本文针对大规模拣选任务时固定货架的拣选路径优化，提出一种分解—合成的方法：根据货物在货架中的位置分为几部分，用遗传算法得到组内的满意解，再用启发式算法将各部分连成一条回路，得到最后的满意解。实验结果表明，与简单遗传算法相比，该算法的性能及优化率都得到了极大的提高。
配送运输是配送中心送货出门的最后一道程序，因此配送效率的高低直接影响配送的质量。对其行驶路线路进行优化将极大地降低运输成本，提高运输效率。本文对不同数量运输任务的车辆行驶线路进行了优化。在初始种群的产生时，采用聚类的方法，从实验结果可以出，与简单的遗传算法相比，对不同数量的运输任务，该算法的优化率有不同程度的提高。
In this dissertation, several aspects of chain store running and logistics distribution center such as the concept, the features, the functions and the operation process are introduced at first. Some scheduling optimization problems of logistics distribution center such as order-picking for multi-level carousel with two server order-picking for fixed shelves and vehicle scheduling for distribution traffic are indicated.
The order-picking route optimization for carousel and fixed shelves can largely improve the efficiency of the automated warehouse. The multi-level carousel is the latest development in the automated warehouse. It is specifically applied to store small parts. The literatures on order-picking problem of the carousel were mainly concentrated on the single server, few papers were devoted to the case of two servers. In this paper, based on two-level genetic algorithm, an improved approach is proposed to order-picking optimization of multi-level carousel system with two servers. The heuristic method was first used in single carousel optimization, and then genetic algorithm was used in entirety optimization. The results of the computer simulation show that it can deeply shorten the time of sorting out.
Fixed shelves have large proportion in cubic warehouse and many goods store in it especially large goods. A new approach is proposed in this paper for extensive order-picking optimization of fixed shelves system. The whole indenture is firstly separated into some sub-indenture, and genetic algorithm was used to optimize every sub-indenture, then heuristic method was used to connect optimized sub-indenture. The results of numerical simulations show the validity of this approach.
Distribution traffic is the last program for distribution center sending the goods out. The efficiency of traffic will affect the quality of distribution. The route optimization for traffic can reduce traffic cost and advance traffic efficiency. For this purpose, an improved genetic algorithm is given to optimize the distribution route for different traffic task. The numerical
results of different size show the validity of improved algorithm comparing with simple genetic algorithm.
引文
[1].Ue-Pyng Wen. Order picking for a Two-Carousel-Server-System in an automated warehouse.Proceedings of the 10th.International conference on automation in Dallas, texas,U.S.A, 1989:64-70.
[2].Ue-pyng Wen, Chang Ding-Tsair.Picking rules for a carousel conveyor in an automated warehouse, OMEGA Int.J. of Mgmt Sci., Vol.16, No.2, 1988:145-151.
[3].Stephen M.Hart, Chuen Lung S.Chen.Simulated annealing and the mapping problem: a computational study. Computers Ops Res.Vol.21, No.4, 1994:455-461.
[4].Chee-Kit Looi. Neural network methods in combinatorial optimization.Computers Ops Res.Vol.19, No.3-4, 1992: 191-208.
[5].Gelletly J. An overview of genetic algorithms and their applications. Kybernetes, Vol.21, No.6, 1992:26-30.
[6].AntoonKolen, Erwin Pesch. Genetic local search in combinatorial optimization. Discrete Applied Mathematics 48, 1994:273-284.
[7].Changyou Liu,Yunwei Shang, Jiaheng Lin.Intelligent optimizing methods for vehicle scheduling problems in antomated warehouse.Proceedings of IEE Control Conference 2002, Hong Kong, Hang Zhou, 52-56.
[8].S.Kirkpatrick etal, Optimization by simulated annealing, Science, Vol.22, 671-680,1983.
[9].Tian Guohui,etal,Research and application of optimal technique on automated warehouse, Proceedings International Conference onModelling,Simulation and Control", AMSE,1:93-96, 1993.
[10].David.E.Van den Bout, T.K.Miller, A traveling salesman objective functions that works, Proc. IEEE Int. Conf. Neural Networks, San Diego, Calif., Vol.2, 1988.
[11].R.Durbin&D.Willshaw, An analogue approach to the traveling salesman problem using an elastic net method.Nature, Vol.326, 689-691, 1987.
[12].Malmborg, Charles, Genetic Algorithm for Service Level Based Vehicle Scheduling, European Journal of Operational Research, Vol.93, No.1, 1996,121-134.
[13].J.J.Hopfield and D.W.Tank, Neural Computation of Decisions in Optimization problem, Biological Cybemetics, Vol.52, 141-152, 1985.
[14].Altinkemer K.,Gavish B.,Parallel Savings Based Heuristic for the Delivery Problem,Operations Research, 1991, Vol.39, 456-459.
[15].Barbarosoglu, Gulay, Ozgur,Tabu search Algorithm for The Vehicle Routing Problem, Computer&Operations Research, 1999, Vol.26, No.3, 255-270.
[16].Bramel J.,Simchi-Levi D.,A Location Based Heuristic for General Routing Problems, Operations Research.1995, Vol.43, 649-660.
[17].Cesar Rego, A Subpath Ejection Method for The Vehicle Routing Problem, Management Science, 1998, Vol.44, No.10, 1447-1459.
[18].Fiechter, A parallel tabu search algorithm for large traveling salesman problem, Discrete Application Mathematics, 1994, Vol.51, 243-267.
[19].Osman I.H., Metastrategy Simulated Annealing and Tabu Search Algorithms for The Vehicle Routing Problem, Ann.Operations Research, 1993, Vol.41, 421-451.
[20].Renaud J., Boctor F., Laporte G., An Improved Petal Heuristic forThe Vehicle Routing. Journal of Operational Research Society, 1996, Vol.17, 329-336.
[21].Taillard E., Parallel Iterative Search Methods for Vehicle Routing Problem, Networks,1993, Vol.23, No.1, 661-673.
[22].Fogel D.E., Applying Evolutionary Programming to Selected TSP.Cybern and Syst: An Inter ational Journal, 1993, Vol.24,367-384.
[23].Wilson G.V., Paw G.S., On the Stability of the TSP Algorithm of Hopfield and Tank.Biol Cybern, 1988, Vol.58, 63-70.
[24].Helman I.Sterb.Parts location and optimal picking rules for a carousel conveyor automation storage and retrival system.Proceedings of 7th international conference on automation in warehousing, 1986, 363-376.
[25]Goldberg, D.E. Genetic algorithms in search, optimization, and machine learning, Msssachusetts, Addison-Wesley publishing company, Inc.1989.
[26]Gillet B.E., Miller L.R., A Heuristic Algorithm for the Vehicle Dispatch Problem,Operations Research, Vol.22, 1974;340-349.
[27]Torki, Abdolhamid, Somhon, Competitive Neural Network Algorithm for Solving Vehicle Routing Problem, Computers&Industrial Engineering, Vol.33, No.3-4, 1997, 473-476.
[28]．窦金凤，曹家宝，动态规划在立体仓库管理中的应用，基础自动化，Vol．8，No．6，2001，28-30．
[29]．俞仲文，陈代芬，物流配送技术与实务，2001．
[30]．恽为民，席裕庚，遗传算法的全局收敛性和计算效率的分析．控制理论与应用，Vol13，No．4，1996，455-460．
[31]．霍佳震，殷豪，刘仲英，连锁超市配送中心管理信息系统的设计与研究，计算机应用与研究，1999，2，73-75．
[32]．王钊，单伺服机分层旋转货架存取路径的研究，山东工业大学硕士学位论文，1995．
[33]．孙艳丰，郝江凌，大型复杂结构优化问题的遗传算法，北方交通大学学报，Vol 21，No．6，1997，616-620．
[34]．孙艳丰，王众托，遗传算法在优化问题中的应用研究进展，控制与决策，Vol11,No．4，1996，425-431．
[35]．林家恒，王钊，刘长有，旋转货架存取的一种优化方法，中国控制与决策学术年会论文集．东北大学出版社，1995，412-415．
[36]．林家恒，李国峰，刘长有，双伺服机分层旋转货架拣选路径优化的两级遗传算法，控制与决策，Vol．12，No.4，1997，332-336．
[37]．赵赫，杜端甫，遗传算法求解旅行推销员问题时算子的设计和选择，系统工程理论与实践，Vol．18，No．2，1998，62-65．
[38]谢秉磊，李军，郭耀煌，遗传算法在非满载车辆线路安排问题中的应用，中国学术期刊，Vol．5，No．8，1999，1068-1069．
[39]．陈良元，黄叔武等，商业连锁计算机管理系统，机械工业出版社，1996．
[40]．周金荣，黄道，蒋慰宽，遗传算法的改进及其应用研究，控制与决策，Vol．10，No．3，1995，261-264．
[41]．L．R．富尔兹著，沈明刚，周素琴，孙根娣译，张建中校，组和最优化，上海翻译出版社．
[42]吴晓涛，孙增圻，用遗传算法进行路径规划，清华大学学报，Vol．35，No．5，1995，14-19．
[43]李军，郭耀煌，物流配送车辆优化调度理论与方法，中国物资出版社，2001．
[44]．丁立言，张铎，物流基础，清华大学出版社，2000．
[45]．商允伟，自动化立体仓库固定货架系统的作业调度优化问题研究，山东工业大学硕士学位论文，1996．
[46]．姜大立，杨西龙，车辆路径问题的遗传算法研究，系统工程理论与实践，Vol．19，No．2，1999，40-45．
[47]．张震，城市货运汽车营运组织最优化的理论方法，管理工程学报，Vol．9，No．3，1995，143-152．
[48]．李大卫，王莉，王梦光，一个求解带有时间窗口约束的车辆路径问题的启发式算法，系统工程，1998，Vol6，No．4，20-24．
[49]．靳蕃，范俊波，谭永东，神经网络与神经计算机原理应用，西南交通大学出版社，1991．
[50]蔡延光，钱积新，孙优贤，多重运输调度问题基于双表的并行表搜索算法，系统工程理论与实践，Vol．18，No．11，1998，20-26．
[51]．李军，车辆调度问题的分派启发式算法，系统工程理论与实践，1999，Vol．19，No．1，27-33
[2].Ue-pyng Wen, Chang Ding-Tsair.Picking rules for a carousel conveyor in an automated warehouse, OMEGA Int.J. of Mgmt Sci., Vol.16, No.2, 1988:145-151.
[3].Stephen M.Hart, Chuen Lung S.Chen.Simulated annealing and the mapping problem: a computational study. Computers Ops Res.Vol.21, No.4, 1994:455-461.
[4].Chee-Kit Looi. Neural network methods in combinatorial optimization.Computers Ops Res.Vol.19, No.3-4, 1992: 191-208.
[5].Gelletly J. An overview of genetic algorithms and their applications. Kybernetes, Vol.21, No.6, 1992:26-30.
[6].AntoonKolen, Erwin Pesch. Genetic local search in combinatorial optimization. Discrete Applied Mathematics 48, 1994:273-284.
[7].Changyou Liu,Yunwei Shang, Jiaheng Lin.Intelligent optimizing methods for vehicle scheduling problems in antomated warehouse.Proceedings of IEE Control Conference 2002, Hong Kong, Hang Zhou, 52-56.
[8].S.Kirkpatrick etal, Optimization by simulated annealing, Science, Vol.22, 671-680,1983.
[9].Tian Guohui,etal,Research and application of optimal technique on automated warehouse, Proceedings International Conference onModelling,Simulation and Control", AMSE,1:93-96, 1993.
[10].David.E.Van den Bout, T.K.Miller, A traveling salesman objective functions that works, Proc. IEEE Int. Conf. Neural Networks, San Diego, Calif., Vol.2, 1988.
[11].R.Durbin&D.Willshaw, An analogue approach to the traveling salesman problem using an elastic net method.Nature, Vol.326, 689-691, 1987.
[12].Malmborg, Charles, Genetic Algorithm for Service Level Based Vehicle Scheduling, European Journal of Operational Research, Vol.93, No.1, 1996,121-134.
[13].J.J.Hopfield and D.W.Tank, Neural Computation of Decisions in Optimization problem, Biological Cybemetics, Vol.52, 141-152, 1985.
[14].Altinkemer K.,Gavish B.,Parallel Savings Based Heuristic for the Delivery Problem,Operations Research, 1991, Vol.39, 456-459.
[15].Barbarosoglu, Gulay, Ozgur,Tabu search Algorithm for The Vehicle Routing Problem, Computer&Operations Research, 1999, Vol.26, No.3, 255-270.
[16].Bramel J.,Simchi-Levi D.,A Location Based Heuristic for General Routing Problems, Operations Research.1995, Vol.43, 649-660.
[17].Cesar Rego, A Subpath Ejection Method for The Vehicle Routing Problem, Management Science, 1998, Vol.44, No.10, 1447-1459.
[18].Fiechter, A parallel tabu search algorithm for large traveling salesman problem, Discrete Application Mathematics, 1994, Vol.51, 243-267.
[19].Osman I.H., Metastrategy Simulated Annealing and Tabu Search Algorithms for The Vehicle Routing Problem, Ann.Operations Research, 1993, Vol.41, 421-451.
[20].Renaud J., Boctor F., Laporte G., An Improved Petal Heuristic forThe Vehicle Routing. Journal of Operational Research Society, 1996, Vol.17, 329-336.
[21].Taillard E., Parallel Iterative Search Methods for Vehicle Routing Problem, Networks,1993, Vol.23, No.1, 661-673.
[22].Fogel D.E., Applying Evolutionary Programming to Selected TSP.Cybern and Syst: An Inter ational Journal, 1993, Vol.24,367-384.
[23].Wilson G.V., Paw G.S., On the Stability of the TSP Algorithm of Hopfield and Tank.Biol Cybern, 1988, Vol.58, 63-70.
[24].Helman I.Sterb.Parts location and optimal picking rules for a carousel conveyor automation storage and retrival system.Proceedings of 7th international conference on automation in warehousing, 1986, 363-376.
[25]Goldberg, D.E. Genetic algorithms in search, optimization, and machine learning, Msssachusetts, Addison-Wesley publishing company, Inc.1989.
[26]Gillet B.E., Miller L.R., A Heuristic Algorithm for the Vehicle Dispatch Problem,Operations Research, Vol.22, 1974;340-349.
[27]Torki, Abdolhamid, Somhon, Competitive Neural Network Algorithm for Solving Vehicle Routing Problem, Computers&Industrial Engineering, Vol.33, No.3-4, 1997, 473-476.
[28]．窦金凤，曹家宝，动态规划在立体仓库管理中的应用，基础自动化，Vol．8，No．6，2001，28-30．
[29]．俞仲文，陈代芬，物流配送技术与实务，2001．
[30]．恽为民，席裕庚，遗传算法的全局收敛性和计算效率的分析．控制理论与应用，Vol13，No．4，1996，455-460．
[31]．霍佳震，殷豪，刘仲英，连锁超市配送中心管理信息系统的设计与研究，计算机应用与研究，1999，2，73-75．
[32]．王钊，单伺服机分层旋转货架存取路径的研究，山东工业大学硕士学位论文，1995．
[33]．孙艳丰，郝江凌，大型复杂结构优化问题的遗传算法，北方交通大学学报，Vol 21，No．6，1997，616-620．
[34]．孙艳丰，王众托，遗传算法在优化问题中的应用研究进展，控制与决策，Vol11,No．4，1996，425-431．
[35]．林家恒，王钊，刘长有，旋转货架存取的一种优化方法，中国控制与决策学术年会论文集．东北大学出版社，1995，412-415．
[36]．林家恒，李国峰，刘长有，双伺服机分层旋转货架拣选路径优化的两级遗传算法，控制与决策，Vol．12，No.4，1997，332-336．
[37]．赵赫，杜端甫，遗传算法求解旅行推销员问题时算子的设计和选择，系统工程理论与实践，Vol．18，No．2，1998，62-65．
[38]谢秉磊，李军，郭耀煌，遗传算法在非满载车辆线路安排问题中的应用，中国学术期刊，Vol．5，No．8，1999，1068-1069．
[39]．陈良元，黄叔武等，商业连锁计算机管理系统，机械工业出版社，1996．
[40]．周金荣，黄道，蒋慰宽，遗传算法的改进及其应用研究，控制与决策，Vol．10，No．3，1995，261-264．
[41]．L．R．富尔兹著，沈明刚，周素琴，孙根娣译，张建中校，组和最优化，上海翻译出版社．
[42]吴晓涛，孙增圻，用遗传算法进行路径规划，清华大学学报，Vol．35，No．5，1995，14-19．
[43]李军，郭耀煌，物流配送车辆优化调度理论与方法，中国物资出版社，2001．
[44]．丁立言，张铎，物流基础，清华大学出版社，2000．
[45]．商允伟，自动化立体仓库固定货架系统的作业调度优化问题研究，山东工业大学硕士学位论文，1996．
[46]．姜大立，杨西龙，车辆路径问题的遗传算法研究，系统工程理论与实践，Vol．19，No．2，1999，40-45．
[47]．张震，城市货运汽车营运组织最优化的理论方法，管理工程学报，Vol．9，No．3，1995，143-152．
[48]．李大卫，王莉，王梦光，一个求解带有时间窗口约束的车辆路径问题的启发式算法，系统工程，1998，Vol6，No．4，20-24．
[49]．靳蕃，范俊波，谭永东，神经网络与神经计算机原理应用，西南交通大学出版社，1991．
[50]蔡延光，钱积新，孙优贤，多重运输调度问题基于双表的并行表搜索算法，系统工程理论与实践，Vol．18，No．11，1998，20-26．
[51]．李军，车辆调度问题的分派启发式算法，系统工程理论与实践，1999，Vol．19，No．1，27-33