摘要
经济发展推动着制造企业的全球化进程,企业间的竞争随之转变为企业所在供应链间的竞争。供应链管理水平的高低直接决定了供应链竞争能力的强弱。如何有效地管理和优化供应链成为企业经营者关注的热点问题。分销系统负责满足客户需求,完成从产品到商品的转换,其作为连接生产商与消费者的桥梁是供应链完成增值的重要部分。分销系统中库存与运输成本在物流成本中占据了相当高的比例,对分销系统的有效管理和优化是供应链管理的关键问题,分销系统中的优化问题则成为理论研究的焦点。然而分销系统是一个复杂的系统,有很多因素需要在优化中进行考虑且不能被简单地忽略,与此同时新的管理及运作方式不断涌现,使得已有的研究与决策不能很好地适用于新的环境及条件,这导致企业对新环境或新管理运作模式下分销系统的决策与优化需求日益迫切。
有鉴于此,本文以生产分销型企业为研究背景,运用优化理论及方法,系统地研究了分销系统中考虑货物权重的车辆路径决策及租赁车辆运输运作模式下的集成库存运输问题。本文的主要工作包括:
(1)围绕路径问题和集成库存运输问题从模型和算法两方面进行综述及研究,介绍车辆路径问题的不同分类方法,车辆路径问题的基本扩展及不同建模方法。介绍根据研究侧重点不同而形成的两类集成存储分销问题的研究情况。研究了车辆路径问题及集成存储分销问题的求解算法。上述工作为关键问题研究提供了理论和方法支持。
(2)详细阐述了带货物权重车辆路径问题的研究背景,提出了无能力约束的带货物权重车辆路径问题的模型,并按照两种求解思路,即通过修改求解旅行商问题的节约算法和一种粒子群算法以及考虑问题特征设计的启发式对问题进行求解,说明问题研究的必要性。提出了求解具有能力约束的带货物权重车辆路径问题的分散搜索算法,将考虑货物权重的启发式规则嵌入分散搜索算法框架中,通过与其他求解同类问题的算法比较,验证算法的有效性;并对模型的适用条件进行了分析。
(3)以带货物权重车辆路径问题为基础,将该问题中的车场从一个扩展为多个,并考虑路径长度限制,提出了多车场具有路径长度限制的带货物权重车辆路径问题模型。为了对该问题求解,首先设计了求解多车场车辆路径问题的分散搜索算法,并采用标准数据集测试,验证了算法的有效性。然后将该分散搜索算法结合求解具有能力约束的带货物权重车辆路径问题的分散搜索算法,提出了求解多车场带货物权重车辆路径问题的分散搜索算法。重点分析了货物权重参数变化对总费用的影响,模型的适用条件及分散搜索算法的性能。
(4)研究了不同运输运作模式下集成库存运输问题,重点比较和分析针对同一个问题,选择不同运输模式之间的差别。通过对相同计划下不同模式的总费用分析、不同运输模式最优解之间的关系以及租赁车辆运输模式中参数变化对总费用影响的研究,得出了不同运输模式在不同条件下的适用性及运输模式选择需要注意的因素。与此同时给出度量方法,指导企业对运输运作模式进行选择。
(5)以生产分销型企业为背景,研究了租赁车辆运输模式下,多对多网络结构下,多周期集成库存运输问题。根据对新运作模式的观察,建立了租赁模式下的多仓库无返回库存运输优化问题模型,其中路径部分采用开放式车辆路径问题建模方法,并提出了基于精英保留策略的遗传算法对问题进行求解。问题采用二维编码方式,基于启发式规则生成初始种群,基于降低库存惩罚费用设计变异操作符。最后采用随机生成的数据对遗传算法进行测试,验证算法的有效性。
The economic development impels the process of the globalization of the manufacturing enterprises. The competition among enterprises has become the competition among the supply chain which the enterprises belong to. The level of supply chain management determines the competitiveness of the supply chain. How to manage and optimize the supply chain effectively becomes a hot issue concerned by the managers of the enterprises. The distribution system meets customers' needs to complete the conversion from product to merchandise. It is an important part to increase the value of the supply chain and it is a bridge between producers and consumers. The inventory and transportation costs in the distribution system account for a relatively high proportion of the logistics costs. The effective management and optimization of the distribution system is the key of the supply chain management. Hence, the optimization problems in the distribution system become a focus of the theoretical study. However, the distribution system is a complex system, and there are many factors to be considered in the optimization and not to be ignored simply. At the same time, the new management and operation continue emerging to make the existing research and decision not be applied to the new environment and condition, which leads to the demand about the decision and optimization on the distribution system under the new environment or operation being urgent increasingly.
For this reason, the production and distribution enterprises are as the background. The vehicle routing decision with weight-related cost and the integrated inventory transportation problem under vehicle-rent operation mode are considered systematically by adopting the theory and method of the optimization. The major work of this paper includes five aspects as follows:
(1) Based on the routing problem and integrated inventory and transportstion problems, the summary and the corresponding research are done from the aspects of the modeling and solution. The different classification methods, the basic extensions of the vehicle routing problem and the different modeling methods are presented. The two types of integrated inventory and distribution problems classified by the different research focus are introduced. The solving algorithms of the vehicle routing problem and the integrated inventory and distribution problem are studied. The above-mentioned work provides a theoretical and methodological support for the research of the key issues.
(2) The detailed description of the background of the vehicle routing problem with weight-ralated cost (VRPWRC) has been given. The model of the weighted traveling salesman problem is presented. Two types of methods are introduced to solve the problem. One type is to modify the solutions of the Traveling Salesman Problem which are CW algorithm and a kind of particle swarm optimization algorithm. The other is to design a heuristic by considering the characteristic of the problem. The reason of studying the problem is given. The scatter search algorithm for the vehicle routing problem with weight-related cost is proposed. The heuristic rule considering the weight-related cost is embedded in the framework of scatter search algorithm. The comparison with other algorithms for the same problem is to verify the validity of the scatter searcfi algorithm. The applicability of the model is analyzed.
(3) Based on the vehicle routing problem with weight-ralated cost, the multi-depot vehicle routing problem with weight-ralated cost is proposed that the depot of the VRPWRC is extended from one to multiple and the constraint of the route length is considered. To solve the problem, the solving algorithm of the multi-depot vehicle routing problem is studied first. The benchmark problems of the multi-depot vehicle routing problem are used to test the scatter search algorithm and to verify the validity of the algorithm. Considering the scatter search algorithms for the multi-depot vehicle routing problem and for the VRPWRC, the scatter search for the multi-depot vehicle routing problem with weight-ralated cost is proposed. The effect of varying the parameter of weight-related cost on the total cost and the applicability of the model are analyzed. The performance of the proposed algorithm is also studied.
(4) The integrated inventory and transportation problem with different operation mode of transportation is studied. It focuses on comparing and analyzing the difference adopting the different operation mode of transportation for the same problem. The applicability of the different operation mode of transportation under the different conditions is obtained by analyzing the total cost of the different operation of transportation with the same plan, the relationship among the optimal solutions of the different operation mode of transportation and the effect of varying the parameters on the total cost under vehicle-rent operation mode. The factors that affect the selection of the operation mode of transportation are presented. The method of the measurement is introduced to guide the enterprises to select the operation mode of transportation.
(5) The multi-period integrated inventory transportation problem with the vehicle-rent operation mode and the many-many network structure is considered in production and distribution enterprise. Based on the observation to the new operation mode of transportation, the inventory and multi-depot open transportation problem with vehicle-rent (IMDOT-VR) is proposed. The transportation part is modeled by the open vehicle routing problem. A genetic algorithm with elitist preservation strategy is developed for IMDOT-VR. The solution is coded by two-dimensional coding. The initial population is generated by the heuristic rule. The mutation operator is designed to reduce the inventory and penalty cost. The random data is used to verify the effectiveness of the algorithm.
引文
1.马士华,林勇.供应链管理IIM],北京:高等教育出版社,2003.
2.魏志强,王先逵,吴丹,杨志刚.面向全球制造环境的先进制造使能技术[J],中国机械工程,2001,12(007):760-765.
3.杨叔子,吴波,胡春华,程涛.网络化制造与企业集成[J],中国机械工程,2000,11(001):45-48.
4.白英彩,唐冶文,余巍.计算机集成制造系统[M],北京:清华大学出版社,1997.
5.甄造堂.美国企业的准时生产制(JIT)[J],价值工程,1996,(005):42-42.
6.高峻峻.不确定性需求下供应链中分销系统的建模与仿真[D],沈阳:东北大学,2004.
7.施先亮,李伊松.供应链管理原理及应用[M],北京:清华大学出版社,2006.
8.高慧颖.分销渠道中的物流网络优化与分销商选择研究[D],上海:上海海运学院,2003.
9.陈国权.供应链管理[J],中国软科学,1999,10:101-104.
10.Desrochers M,Lenstra J K,Savelsbergh M W P.A classification scheme for vehicle routing and scheduling problems[J],European Journal of Operational Research,1990,46(3):322-332.
11.Toth P,Vigo D.The vehicle routing problem[M],Philadelphia:SIAM,2002.
12.Eksioglu B,Vural A,Reisman A.The vehicle routing problem:A taxonomic review[J],Computers & Industrial Engineering,2009,57:1472-1483.
13.Silver E.Operations research in inventory management:a review and critique[J],Operations Research,1981,29(4):628-645.
14.Minner S.Multiple-supplier inventory models in supply chain management:A review[J],International Journal of Production Economics,2003,81:265-279.
15.Stadtler H,Kilger C.Supply chain management and advanced planning:concepts,models,software and case studies[M],Berlin Heidelberg:Springer Verlag,2005.
16.Abdelmaguid T F,Dessouky M M.A genetic algorithm approach to the integrated inventory-distribution problem[J],International Journal of Production Research,2006,44(21):4445-4464.
17.Viswanathan S,Mathur K.Integrating routing and inventory decisions in one-warehouse multiretailer multiproduct distribution systems[J],Management Science,1997:294-312.
18.Chen Z L,Vairaktarakis G L.Integrated scheduling of production and distribution operations[J],Management Science,2005,51(4):614-628.
19.Yokoyama M.Integrated optimization of inventory-distribution systems by random local search and a genetic algorithm[J],Computers & Industrial Engineering,2002,42(2-4):175-188.
20.Lenstra J K,Kan A H G R.Complexity of vehicle routing and scheduling problems[J],Networks,1981,11(2):221-227.
21.Lee E.Branch-and-bound methods[J],Handbook of Applied Optimization,2002:53-65.
22.Bellman R.Some applications of the theory of dynamic programming-a review[J],Journal of the Operations Research Society of America,1954,2(3):275-288.
23.Dantzig G B,Ramser J H.The Truck Dispatching Problem[J],Management Science,1959,6(1):80-91.
24.谢秉磊,郭耀煌.动态车辆路径问题:现状与展望[J],系统工程理论方法应用, 2002,11(002):116-120.
25.郎茂祥,胡思继.车辆路径问题的禁忌搜索算法研究[J],管理工程学报,2004,18(001):81-84。
26.Lee L,Tan K,Ou K,Chew Y.Vehicle capacity planning system:A case study on vehicle routing problem with time windows[J],IEEE Transactions on Systems,Man and Cybernetics,Part A,2003,33(2):169-178.
27.Angelelli E,Speranza M.The application of a vehicle routing model to a waste-collection problem:two case studies[J],Journal of the Operational Research Society,2002,53(9):944-952.
28.Wade A,Salhi S.An investigation into a new class of vehicle routing problem with backhauls[J],Omega,2002,30(6):479-487.
29.Laporte G.The vehicle routing problem:An overview of exact and approximate algorithms[J],European Journal of Operational Research,I992,59(3):345-358.
30.Cordeau J F,Gendreau M,Laporte G,Potvin J Y,Semet F.A guide to vehicle routing heuristics[J],Journal of the Operational Research Society,2002,53(5):512-522.
31.郭辉煌,李军.车辆优化调度问题的研究现状评述[J],西南交通大学学报,1995,30(004):376-382.
32.Bodin L.A taxonomic structure for vehicle routing and scheduling problems[J],Computers and Urban Society,1975,1:11-29.
33.Bodin L,Golden B.Classification in vehicle routing and scheduling[J],Networks,1981,11(2):97-108.
34.Gendreau M,Laporte G,Seguin R.Stochastic vehicle routing[J],European Journal of Operational Research,1996,8,8(1):3-12.
35.祝崇隽,刘民.供应链中车辆路径问题的研究进展及前景[J],计算机集成制造系统,2001,7(011):1-6.
36.刘云忠,宣慧玉.车辆路径问题的模型及算法研究综述[J],管理工程学报,2005,19(001):124-130.
37.孙丽君,胡祥培,王征.车辆路径规划问题及其求解方法研究进展[J],系统工程,2006,24(011):31-37.
38.刘兴.基于协作的车辆路径问题研究[D],天津:天津大学,2006.
39.刘霞.车辆路径问题的研究[D],武汉:华中科技大学,2007.
40.曹二保.物流配送车辆路径问题模型及算法研究[D],长沙:湖南大学,2008.
41.娄山佐.车辆路径问题的建模及优化算法研究[D],西安:西北工业大学,2006.
42.李相勇.车辆路径问题模型及算法研究[D],上海:上海交通大学,2007.
43.马华伟.带时间窗车辆路径问题及其启发式算法研究[D],合肥:合肥工业大学,2008.
44.李永先.车辆路径问题的仿真模型及优化方法研究[D],大连:大连理工大学,2007.
45.Renaud J,Laporte G,Boctor F F.A tabu search heuristic for the multi-depot vehicle routing problem[J],Computers and Operations Research,1996,23(3):229-235.
46.符卓.带装载能力约束的开放式车辆路径问题及其禁忌搜索算法研究[J],系统工程理论与实践,2004,24(003):123-128.
47.Cordeau J F,Laporte G,Savelsbergh M W P,Vigo D,Vehicle Routing[A].Barnhart C.Laporte G.Transportation,Handbooks in Operations Research and Management Science[C].Amsterdam:Elsevier,2007,367-428.
48.Ordonez F,Sungur I,Dessouky M.A priori performance measures for arc-based formulations of fehicle routing problem[J],Transportation Research Record:Journal of the Transportation Research Board,2007,2032(-1):53-62.
49.Campbell A M,Savelsbergh M W P.A decomposition approach for the inventory-routing problem [J], Transportation Science, 2004, 38(4): 488-502.
50. Campbell A, Clarke L, Kleywegt A, Savelsbergh M. The inventory routing problem [J], Fleet management and logistics, 1998: 95-113.
51. Webb I, Larson R. Period and phase of customer replenishment: A new approach to the strategic inventory/routing problem [J], European Journal of Operational Research, 1995, 85(1): 132-148.
52. Golden B, Assad A, Dahl R. Analysis of a large scale vehicle routing problem with an inventory component [J], Large Scale Systems, 1984, 7(2-3): 181-190.
53. Chien T W, Balakrishnan A, Wong R T. An integrated inventory allocation and vehicle routing problem [J], Transportation Science, 1989, 23(2): 67-76.
54. Dror M, Ball M, Golden B. A computational comparison of algorithms for the inventory routing problem [J], Annals of Operations Research, 1985,4(1): 1-23.
55. Dror M, Ball M. Inventory/routing: reduction from an annual to a short-period problem [J], Naval Research Logistics, 1987, 34(6): 891-905.
56. Dror M, Levy L. A vehicle routing improvement algorithm comparison of a" greedy" and a matching implementation for inventory routing [J], Computers and Operations Research 1986,13(1): 33-45.
57. Trudeau P, Dror M. Stochastic inventory routing: Route design with stockouts and route failures [J], Transportation Science, 1992, 26(3): 171-184.
58. Jaillet P, Huang L, Bard J, Dror M. A rolling horizon framework for the inventory routing problem [R], Department of Management Science and Information Systems, University of Texas, 1997.
59. Bard J, Huang L, Jaillet P, Dror M. A decomposition approach to the inventory routing problem with satellite facilities [J], Transportation Science, 1998, 32(2): 189-203.
60. Sarmiento A, Nagi R. A review of integrated analysis of production-distribution systems [J], IIE Transactions, 1999, 31(11): 1061-1074.
61. Bertazzi L, Speranza M G. Models and algorithms for the minimization of inventory and transportation costs: A survey [J], New trends in distribution logistics, 1999,480: 137-157.
62. Schwarz L, Ward J, Zhai X. Joint transportation-and-inventory problems in supply chains: a review [R], Krannert School of Management, Purdue University, 2004.
63. Kim J U, Kim Y D. A Lagrangian relaxation approach to multi-period inventory/distribution planning [J], Journal of the Operational Research Society, 2000, 51(3): 364-370.
64. Jung J, Mathur K. An efficient heuristic algorithm for a two-echelon joint inventory and routing problem [J], Transportation Science, 2007, 41(1): 55-73.
65. Zhao Q H, Chen S, Zang C X. Model and algorithm for inventory/routing decision in a three-echelon logistics system [J], European Journal of Operational Research, 2008, 191(3): 623-635.
66. Laporte G, Nobert Y. Exact algorithms for the vehicle routing problem [J], Surveys in Combinatorial Optimization, 1.987, 31: 147-184.
67. Laporte G, Gendreau M, Potvin J Y, Semet F. Classical and modern heuristics for the vehicle routing problem [J], International Transactions in Operational Research, 2000, 7(4-5): 285-300.
68. Fischetti M, Toth P, Vigo D. A branch-and-bound algorithm for the capacitated vehicle routing problem on directed graphs [J], Operations Research, 1994,42(5): 846-859.
69. Lysgaard J, Letchford A N, Eglese R W. A new branch-and-cut algorithm for the capacitated vehicle routing problem [J], Mathematical Programming, 2004, 100(2): 423-445.
70. Eilon S, Watson D T, Christofides N. Distribution management: mathematical modelling and practical analysis [M], London: Griffin, 1971.
71. Fisher M. Optimal solution of vehicle routing problems using minimum k-trees [J], Operations Research, 1994, 42(4): 626-642.
72. Laporte G, Semet F, Classical heuristics for the capacitated VRP [A]. Toth P, Vigo D. The Vehicle Routing Problem [C]. Philadelphia: SIAM, 2002,109-128.
73. Clarke G, Wright J W. Scheduling of vehicles from a central depot to a number of delivery points [J], Operations Research, 1964,12(4): 568-581.
74. Yellow P C.A computational modification to the savings method of vehicle scheduling [J], Operational Research Quarterly, 1970,21(2): 281-283.
75. Golden B L, Magnanti T L, Nguyen H Q. Implementing vehicle routing algorithms [J], Networks, 1977, 7(2): 113-148.
76. Paessens H. The savings algorithm for the vehicle routing problem [J], European Journal of Operational Research, 1988, 34(3): 336-344.
77. Nelson M D, Nygard K E, Griffin J H, Shreve W E. Implementation techniques for the vehicle routing problem [J], Computers and Operations Research, 1985,12(3): 273-283.
78. Altinkemer K, Gavish B. Parallel savings based heuristic for the delivery problem [J], Operations Research, 1991, 39: 456-469.
79. Wark P, Holt J. A repeated matching heuristic for the vehicle routeing problem [J], Journal of the Operational Research Society, 1994,45(10): 1156-1167.
80. Gillett B E, Miller L R. A heuristic algorithm for the vehicle dispatch problem [J], Operations Research, 1974, 22(2): 340-349.
81. Lin S. Computer solutions of the traveling salesman problem [J], Bell System Technical Journal, 1965, 44(10): 2245-2269.
82. Lin S, Kernighan B. An effective heuristic algorithm for the traveling-salesman problem [J], Operations Research, 1973, 21: 498-516.
83. Or I. Traveling Salesman-type combinatorial optimization problems and the relation to the logistics of regional blood banking [D], Evanston: Northwestern University, 1976.
84. Renaud J, Boctor F, Laporte G. A fast composite heuristic for the symmetric traveling salesman problem [J], INFORMS Journal on Computing, 1996, 8(2): 134-143.
85. Gendreau M, Hertz A, Laporte G. Tabu search heuristic for the vehicle routing problem [J], Management Science, 1994,40(10): 1276-1290.
86. Taillard E, Badeau P, Gendreau M, Guertin F, Potvin J Y. A tabu search heuristic for the vehicle routing problem with soft time windows [J], Transportation Science, 1997, 31(2): 170-186.
87. Cordeau J F, Gendreau M, Laporte G. A tabu search heuristic for periodic and multi-depot vehicle routing problems [J], Networks, 1997, 30(2): 105-119.
88. Montane F A T, Galvao R D. A tabu search algorithm for the vehicle routing problem with simultaneous pick-up and delivery service [J], Computers and Operations Research, 2006, 33(3): 595-619.
89. Brandao J. A tabu search algorithm for the open vehicle routing problem [J], European Journal of Operational Research, 2004,157(3): 552-564.
90. Brandao J. A deterministic tabu search algorithm for the fleet size and mix vehicle routing problem [J], European Journal of Operational Research, 2009, 195(3): 716-728.
91. Osman I H. Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem [J], Annals of Operations Research, 1993, 41(4): 421-451.
92. Li X Y, Tian P, Leung SCH. An ant colony optimization metaheuristic hybridized with tabu search for open vehicle routing problems [J], Journal of the Operational Research Society, 2009, 60(7): 1012-1025.
93. Wang C H, Lu J Z. A hybrid genetic algorithm that optimizes capacitated vehicle routing problems [J], Expert Systems With Applications, 2009,36(2): 2921-2936.
94. Ghoseiri K, Ghannadpour S F. Hybrid genetic algorithm for vehicle routing and scheduling problem [J], Journal of Applied Sciences, 2009, 9(1): 79-87.
95. Jeon G, Leep H R, Shim J Y. A vehicle routing problem solved by using a hybrid genetic algorithm [J], Computers and Industrial Engineering, 2007, 53(4): 680-692.
96. Berger J, Barkaoui M. A new hybrid genetic algorithm for the capacitated vehicle routing problem [J], Journal of the Operational Research Society, 2003, 54(12): 1254-1262.
97. Tan K C, Lee L H, Ou K. Hybrid genetic algorithms in solving vehicle routing problems with time window constraints [J], Asia-Pacific Journal of Operational Research, 2001, 18(1): 121-130.
98. Chiang W C, Russell R A. Simulated annealing metaheuristics for the vehicle routing problem with time windows [J], Annals of Operations Research, 1996,63: 3-27.
99. Bell J E, McMullen P R. Ant colony optimization techniques for the vehicle routing problem [J], Advanced Engineering Informatics, 2004,18(1): 41-48.
100. Ai T J, Kachitvichyanukul V. A particle swarm optimization for the vehicle routing problem with simultaneous pickup and delivery [J], Computers and Operations Research, 2009,36(5): 1693-1702.
101. Russell R A, Chiang W C. Scatter search for the vehicle routing problem with time windows [J], European Journal of Operational Research, 2006,169(2): 606-622.
102. Braysy O. A reactive variable neighborhood search for the vehicle-routing problem with time windows [J], INFORMS Journal on Computing, 2003,15(4): 347-368.
103. Gendreau M, Laporte G, Seguin R. A tabu search heuristic for the vehicle routing problem with stochastic demands and customers [J], Operations Research, 1996, 44(3): 469-477.
104. Lu L, Tan Q M. Hybrid particle swarm optimization algorithm for stochastic vehicle routing problem [J], Systems Engineering and Electronics, 2006,28(2): 244-247.
105. Moretti Branchini R, Amaral Annentano V, Lokketangen A. Adaptive granular local search heuristic for a dynamic vehicle routing problem [J], Computers and Operations Research, 2009, 36(11): 2955-2968.
106. Zhu C J, Liu M, Wu C, Wu X B. Two kinds of 2-OPT algorithm for VRP with fuzzy demand [J], Acta Electronica Sinica, 2001,29(8): 1035-1037.
107. Zheng Y, Liu B. Fuzzy vehicle routing model with credibility measure and its hybrid intelligent algorithm [J], Applied Mathematics and Computation, 2006,176(2): 673-683.
108. Erbao C, Mingyong L. A hybrid differential evolution algorithm to vehicle routing problem with fuzzy demands [J], Journal of Computational and Applied Mathematics, 2009, 231(1): 302-310.
109. Larsen A. The dynamic vehicle routing problem [D], Copenhagen: The Technical University of Denmark, 2000.
110. Psaraftis H. Dynamic vehicle routing: Status and prospects [J], Annals of Operations Research, 1995, 61(1): 143-164.
111. Larsen A, Madsen O B G, Solomon M M. Recent developments in dynamic vehicle routing systems [J], The Vehicle Routing Problem: Latest Advances and New Challenges, 2008: 199-218.
112. Psaraftis H. Dynamic programming solution to the single vehicle many-to-many immediate request dial-a-ride problem [J], Transportation Science, 1980,14(2): 130-154.
113. Du T C, Li E Y, Chou D. Dynamic vehicle routing for online B2C delivery [J], Omega, 2005, 33(1): 33-45.
114. Coslovich L, Pesenti R, Ukovich W. A two-phase insertion technique of unexpected customers for a dynamic dial-a-ride problem [J], European Journal of Operational Research, 2006,175(3): 1605-1615.
115. Hvattum L, Lokketangen A, Laporte G. Solving a dynamic and stochastic vehicle routing problem with a sample scenario hedging heuristic [J], Transportation Science, 2006, 40(4): 421-438.
116.Jemai J,Mellouli K.A neural-tabu search heuristic for the real time vehicle routing problem[J],Journal of Mathematical Modelling and Algorithms,2008,7(2):161-176.
117.Papastavrou J.A stochastic and dynamic routing policy using branching processes with state dependent immigration[J],European Journal of Operational Research,1996,95(1):167-177.
118.Moin N H,Salhi S.Inventory routing problems:a logistical overview[J],Journal of the Operational Research Society,2007,58(9):1185-1194.
119.Federgruen A,Zipkin P.A Combined vehicle routing and inventory allocation problem[J],Operations Research,1984,32(5):1019-i037.
120.Yu Y,Chen H,Chu F.A new model and hybrid approach for large scale inventory routing problems[J],European Journal of Operational Research,2008,189(3):1022-1040.
121.Baita F,Ukovich W,Pesenti R,Favaretto D.Dynamic routing-and-inventory problems:a review[J],Transportation Research Part A,1998,32(8):585-598.
122.Campbell A,Clarke L,Kleywegt A,Savelsbergh M W P.The inventory routing problem [J],Fleet management and logistics,1998:95-113.
123.潘震东,唐加福,韩毅.带货物权重的车辆路径问题及遗传算法[J],管理科学学报,2007,10(3):23-29.
124.Solomon M.Algorithms for the vehicle routing and scheduling problems with time window constraints[J],Operations Research,1987:254-265.
125.Dror M,Laporte G,Trudeau P.Vehicle routing with split deliveries[J],Discrete Applied Mathematics,1994,50(3):239-254.
126.Li F,Golden B,Wasil E.The open vehicle routing problem:Algorithms,large-scale test problems,and computational-results[J],Computers and Operations Research,2007,34(10):2918-2930.
127.Gaudioso M,Paletta G.A heuristic for the periodic vehicle routing problem[J],Transportation Science,1992,26(2):86-92.
128.王大志.面向实际工程问题的粒子群优化算法应用技术研究[D],沈阳:东北大学,2008.
129.Glover F,Laguna M,Marti R,Scatter Search[A].Ashish G,Shigeyoshi T.Advances in Evolutionary Computing:Theory and Applications[C].New York:Springer-Verlag,2003,519-537.
130.Marti R.Scatter search - Wellsprings and challenges[J],European Journal of Operational Research,2006,169(2):351-358.
131.Glover F.Tabu search for nonlinear and parametric optimization(with links to genetic algorithms)[J],Discrete Applied Mathematics,1994,49(1-3):231-255.
132.Glover F.A template for Scatter Search and Path Relinking[J],Lecture Notes In Computer Science,1998:13-54.
133.Corberan A,Fernandez E,Laguna M,Marti R.Heuristic solutions to the-problem of routing school buses with multiple objectives[J],Journal of the Operational Research Society,2002,53(4):427-435.
134.Alegre J,Laguna M,Pacheco J.Optimizing the periodic pick-up of raw materials for a manufacturer of auto parts[J],European Journal of Operational Research,2007,179(3):736-746.
135.Belfiore P P,Favero L P L.Scatter search for the fleet size and mix vehicle routing problem with time windows[J],Central European Journal of Operations Research,2007,15(4):351-368.
136.Campos V,Corberan A,Mota E,A scatter search algorithm for the split delivery vehicle routing problem[A].Fink A F,Rothlauf F R.Studies in Computational Intelligence[C].Berlin:Springer,2008,137-152.
137.Hamiez J,Hao J.Scatter search for graph coloring[J],Lecture Notes In Computer Science,2002:168-179.
138.Jain A,Meeran S.A multi-level hybrid framework applied to the general flow-shop scheduling problem[J],Computers and Operations Research,2002,29(13):1873-1901.
139.Laguna M,Marti R.Neural network prediction in a system for optimizing simulations[J],Iie Transactions,2002,34(3):273-282.
140.Laguna M,Marti R.The OptQuest callable library[J],Optimization Software Class Libraries,2002:193-218.
141.Sagarna R,Lozano J.Scatter search in software testing,comparison and collaboration with estimation of distribution algorithms[J],European Journal of Operational Research,2006,169(2):392-412.
142.Glover F.Genetic algorithms and scatter search:unsuspected potentials[J],Statistics and Computing,1994,4(2):131-140.
143.Marti R,Laguna M,Campos V.Scatter search vs.genetic algorithms:An experimental evaluation with permutation problems[A].Rego C,Alidaee B.Adaptive Memory and Evolution:Tabu Search and Scatter Search[C],Boston:Kluwer Academic Publishers,2002,263-282.
144.Glover F.A template for scatter search and path relinking[C],Proceedings of the Artificial Evolution,1998,13-54.
145.Zhang X X,Tang L X.A new hybrid ant colony optimization algorithm for the vehicle routing problem[J],Pattern Recognition Letters,2009,30(9):848-855.
146.Belfiore P,Yoshizaki H T Y.Scatter search for a real-life heterogeneous fleet vehicle routing problem with time windows and split deliveries in Brazil[J],European Journal of Operational Research,2009,199(3):750-758.
147.邹彤,李宁,孙德宝,李菁.多车场车辆路径问题的遗传算法[J],计算机工程与应用,2004,21:82-83.
148.Prins C.A simple and effective evolutionary algorithm for the vehicle routing problem [J],Computers and Operations Research,2004,31(12):1985-2002.
149.Marti R,Laguna M,Glover F.Principles of scatter search[J],European Journal of Operational Research,2006,169(2):359-372.
150.Van Breedam A.An analysis of the behavior of heuristics for the vehicle routing problem for a selection of problems with vehicle-related,customer-related,and time-related constraints [D],Antwerp:University of Antwerp,1994.
151.Golden B,Wasil E,Kelly J,Chao I.The impact of metaheuristics on solving the vehicle routing problem:algorithms,problem sets,and computational results[J],Fleet management and logistics,1998:33-56.
152.唐加福,孔媛,潘震东,董颖.基于划分的蚁群算法求解货物权重车辆路径问题[J],控制理论与应用,2008,25(004):699-702.
153.Desaulniers G,Lavigne J,Soumis F.Multi-depot vehicle scheduling problems with time windows and waiting costs[J],European Journal of Operational Research,1998,111(3):479-494.
154.Polacek M,Hartl R F,Doerner K,Reimaun M.A variable neighborhood search for the multi depot vehicle routing problem with time windows[J],Journal of Heuristics,2004,10(6):613-627.
155.Chiu H N,Lee Y S,Chang J H.Two approaches to solving the multi-depot vehicle routing problem with time windows in a time-based logistics environment[J],Production Planning and Control,2006,17(5):480-493.
156.Cordeau J F,Laporte G,Mercier A.Improved tabu search algorithm for the handling of route duration constraints in vehicle routing problems with time windows[J],Journal of the Operational Research Society,2004,55(5):542-546.
157.Dondo R,Cerda J.A cluster-based optimization approach for the multi-depot heterogeneous fleet vehicle routing problem with time windows[J],European Journal of Operational Research,2007,176(3):1478-1507.
158.Wen L,Meng F.An improved PSO for the multi-depot vehicle routing problem with time windows[C],2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application,2008,852-856.
159.Wang X,Xu C,Shang H.Multi-depot vehicle routing problem with time windows and multi-type vehicle number limits and its genetic algorithm[C],2008 International Conference on Wireless Communications,Networking and Mobile Computing,2008,1-5.
160.Dondo R G,Cerda J.A hybrid local improvement algorithm for large-scale multi-depot vehicle routing problems with time windows[J],Computers and Chemical Engineering,2009,33(2):513-530.
161.钟石泉 贺国光.多车场有时间窗的多车型车辆调度及其禁忌算法研究[J],运筹学学报,2005,9(4):67-73.
162.杨元峰,崔志明,陈建明.有时间窗约束的多车场车辆路径问题的改进遗传算法[J],苏州大学学报,2006,26(2):20-23.
163.Lim A,Zhu W.A fast and effective insertion algorithm for multi-depot vehicle routing problem with fixed distribution of vehicles and a new simulated annealing approach[C],Lecture Notes in Computer Science 2006,282-291.
164.Salhi S,Sari M.A multi-level composite heuristic for the multi-depot vehicle fleet mix problem[J],European Journal of Operational Research,1997,103(1):95-112.
165.Crevier B,Cordeau J F,Laporte G.The multi-depot vehicle routing problem with inter-depot routes[J],European Journal of Operational Research,2007,176(2):756-773.
166.段凤华,符卓.有软时窗多车场开放式车辆路径及其禁忌搜索[J],计算机工程与应用,2008,(36):42-44.
167.李延晖,刘向.沿途补货的多车场开放式车辆路径问题及蚁群算法[J],计算机集成制造系统,2008,14(003):557-562.
168.邵宏,李勤真,张福,曾继霞,霍东芳.多车场多配送中心军用物资配送运输研究[J],交通与计算机,2008,26(006):100-104.
169.Nagy G,Salhi S.Heuristic algorithms for single and multiple depot vehicle routing problems with pickups and deliveries[J],European Journal of Operational Research,2005,162(1):126-141.
170.钟石泉,王雪莲.多车场集送一体化车辆调度问题及其遗传算法研究[J],西安电子科技大学学报:社会科学版,2009,(001):63-68.
171.Hadjiconstantinou E,Baldacci R.A multi-depot period vehicle routing problem arising in the utilities sector[J],Journal of the Operational Research Society,1998,49(12):1239-1248.
172.Parthanadee P,Logendran R.Periodic product distribution from multi-depots under limited supplies[J],IIE Transactions,2006,38(11):1009-1026.
173.Mingozzi A.The multi-depot periodic vehicle routing problem[C],Lecture Notes in Computer Science 2005,347-350.
174.Wu T H,Low C,Bai J W.Heuristic solutions to multi-depot location-routing problems [J],Computers and Operations Research,2002,29(10):1393-1415.
175.Liu S C,Lee S B.A two-phase heuristic method for the multi-depot location routing problem taking inventory control decisions into consideration[J],International Journal of Advanced Manufacturing Technology,2003,22(11-12):941-950.
176.陈美军,张志胜,史金飞.多约束下多车场车辆路径问题的蚁群算法研究[J],中国机械工程,2008,19(016):1939-1944.
177.Laporte G,Nobert Y,Arpin D.Optimal solutions to capacitated multidepot vehicle routing problems[J],Congressus Numerantium,1984,44:283-292.
178.Laporte G,Nobert Y,Taillefer S.Solving a family of multi-depot vehicle routing and location-routing problems[J],Transportation Science,1988,22(3):161-172.
179.Baldacci R,Mingozzi A.A unified exact method for solving different classes of vehicle routing problems[J],Mathematical Programming,2009,120(2):347-380.
180.Tillman F A.The multiple terminal delivery problem with probabilistic demands[J],Transportation Science,1969,3(3):192-204.
181.Tillman F A,Hering R W.A study of a look-ahead procedure for solving the multiterminal delivery problem[J],Transportation Research,1971,5:225-229.
182.Tillman F A,Cain T M.An upperbound algorithm for the single and multiple terminal delivery problem[J],Management Science,1972,18(11):664-682.
183.Wren A H A.Computer scheduling of vehicles from one or more depots to a number of delivery points[J],Operational Research Quarterly,1972,23(3):333-344.
184.Gillett B E,Johnson J G.Multi-terminal vehicle-dispatch algorithm[J],Omega,1976,4(6):711-718.
185.Golden B L,Magnanti T L,Nguyen H Q.Implementing vehicle routing[J],Networks,1977,7(2):113-148.
186.Chao I M,Golden B L,Wasil E.A new heuristic for the multi-depot vehicle routing problem that improves upon best-known solutions[J],American Journal of Mathematical and Management Sciences,1993,13(3-4):371-406.
187.Gendreau M,Hertz A,Laporte G.New Insertion and Postoptimization Procedures for the Traveling Salesman Problem[J],Operations Research,1992,40(6):1086-1094.
188.Pisinger D,Ropke S.A general heuristic for vehicle routing problems[J],Computers and Operations Research,2007,34(8):2403-2435.
189.Ombuki-Berman B,Hanshar F,Using Genetic Algorithms for Multi-depot Vehicle Routing[A].Pereira F B,Tavares J.Bio-inspired Algorithms for the Vehicle Routing Problem[C].Berlin:Springer,2009,77-99.
190.钟石泉 贺国光.多车场车辆调度智能优化研究[J],华东交通大学学报,2004,21(6):25-29.
191.邓欣.基于遗传算法的多车场车辆路径问题研究[D],重庆:重庆大学,2007.
192.王介新.蚁群算法求解MDVRP的设计与实现[D],苏州:苏州大学,2007.
193.戴树贵,陈文兰,潘荫荣,胡幼华.多配送中心车辆路径安排问题混合蚁群算法[J],四川大学学报(工程科学版),2008,(06):154-158.
194.Derigs U,Kaiser R.Applying the attribute based hill climber heuristic to the vehicle routing problem[J],European Journal of Operational Research,2007,177(2):719-732.
195.Irnich S,Funke B,Grunert T.Sequential search and its application to vehicle-routing problems[J],Computers and Operations Research,2006,33(8):2405-2429.
196.Christofides N,Eilon S.An algorithm for the vehicle dispatching problem[J],Operational Research Quarterly,1969,20(3):309-318.
197.Chao I M,Golden B L,Wasil E.A new heuristic for the multi-depot vehicle routing problem that improves upon best-known solutions[J],American Journal of Mathematical and Management Sciences,1993,13(3-4):371-406.
198.邓欣,朱征宇,曾凡超.一种多车场路径问题的单亲遗传算法[J],交通与计算机,2007,25(1):31-35.
199.Lim A,Wang F.Multi-depot vehicle routing problem:A one-stage approach[J],IEEE Transactions on Automation Science and Engineering,2005,2(4):397-402.
200.邹彤,李宁,孙德宝.不确定车辆数的有时间窗车辆路径问题的遗传算法[J],系统工程理论与实践,2004,24(6):134-138.
201.卢厚清.“运输”问题的优化模型、算法及其在现代集成制造系统中的应用[D],南 京:南京航空航天大学,2005.
202.Harris F W.How Many Parts To Make At Once[J],Factory,The Magazine of Management,1913,10(2):135-136.
203.Tang J,Yung K,Liu S.Lagrange relaxation decomposition for synchronized production and transportation planning with flexible vehicles[C],International Conference on Services Systems and Services Management,2005,357-361.
204.Bagley J D.The behavior of adaptive systems which employ genetic and correlation algorithms[D],Michigan:University of Michigan,1967.
205.Holland J.Adaptation in Natural and Artificial Systems[M],Michigan:University of Michigan Press,1975.
206.汪定伟,王俊伟,王洪峰.智能优化方法[M],北京:高等教育出版社,2007.
207.De Jong K A.Analysis of the behavior of a class of genetic adaptive systems[D],Michigan:University of Michigan,1975.