用户名: 密码: 验证码:
邮政物流车辆路径问题研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
邮政物流是运筹学和现代物流的重要应用领域之一,其车辆路径问题是一类理论与生产实际联系紧密、复杂条件下的多约束、多目标车辆路径问题。涉及的约束条件和影响因素主要有时间窗、车辆装载容量、道路交通状况、多邮件类型、往返归集、混合搭载、自然条件等。目前,邮政物流车辆路径问题的研究工作还在不断深入,特别是在如何处理往返归集、时间窗和不可预知的自然因素影响,以及设计简单有效的求解算法等方面仍有待进一步研究。本文基于现代物流倡导的系统化思想,针对带硬时间窗约束的邮件车辆路径问题、多目标邮政物流混合车辆路径问题和带软时间窗约束的动态邮政物流混合车辆路径问题,从邮政物流具体实践中抽象实际问题,利用车辆路径问题领域的已有成果,建立了相应的数学模型,并利用多目标遗传算法和自适应多态蚁群算法进行求解,提出了进一步的优化策略。本文同时以四川省邮政公司2008年5月共11个地市雅芳一体化邮政混合物流为例,对邮政物流车辆路径问题进行了计算求解,结合邮政实际生产中的车辆路径问题,分析了不同优化策略对总体邮运费用和实际使用车辆数的影响。
     本文的主要研究内容如下:
     第1章绪论部分,整理与归纳了有关邮政网络、邮政物流、国内外的车辆路径问题研究现状和求解算法等的文献与理论成果,分析了多约束多目标邮政物流混合车辆路径问题的潜在研究领域,提出了本文的主要研究内容和技术实现路线。
     第2章,对邮政车辆运输问题进行了分析和研究,描述了邮政车辆运输问题特征、分类和影响因素等,分析了邮发报刊对运输投递和邮运生产的影响。并以四川省邮政公司11个地市邮政车辆运输费用结算为例,计算了各点实际的月度邮运成本费用,提出了邮政车辆运输问题的一般模型。
     第3章,结合四川省邮政公司11个地市邮件车辆运输时限规定以及车辆往返情况,引入时间窗限制和往返归集等约束条件,建立了带时间窗约束的邮件车辆路径问题模型,并设计以遗传算法为基础的求解策略,对其邮路优化问题进行了对比分析。同时对突发事件和地震等不可抗力因素对邮件车辆路径问题的影响进行了分析。
     第4章针对实际邮政物流车辆调度多优化目标的特性,分析了在现有邮路运输的基础上加载一体化邮政物流项目需求后的车辆调度与路径选择优化问题,构建了带时间约束、多目标邮政物流混合车辆路径问题模型,并以2008年5月四川省邮政公司雅芳一体化混合物流为例,利用自适应多态蚁群算法对带时间约束多目标邮政物流混合车辆路径问题进行了求解,也分析了不同邮件类型对邮政物流混合车辆路径问题的影响。
     第5章,针对带软时间窗约束的动态邮政物流混合车辆路径问题,建立了带时间窗惩罚的最小车辆运输费用模型,考虑了车辆装载容量、时间窗、往返货物归集、邮件与物流商品混合搭载、时间窗惩罚等约束条件,利用遗传算法对模型进行了求解计算和优化对比分析。
     第6章,结合理论分析和实践情况,对比分析了邮政实际生产运输问题、带时间窗约束的邮件车辆路径问题、多目标邮政物流混合车辆路径问题和动态邮政物流混合车辆路径问题的总邮运费用、参与运输的邮运车辆数和优化策略,提出了实际邮运生产的4项优化措施。
     最后,对本文的主要创新之处进行了归纳,并对未来研究作了展望,将多品种、多优先级、多时限要求的邮政物流混合搭载问题等作为下一步研究的重点。
Post logistics is one of the important applications of operational researches and logistics studies. Post logistics vehicle routing problem (VRP) is a multi-restricted conditions and multi-objective problem that strongly correlates the theoretical research and the production practice in complicated conditions. The main restricted conditions and influencing factors include time windows, vehicle loading capacity, road traffic, stochastic demand, round-trip collection, mixed loading, natural conditions, and so on. The study on the VRP has been doing in depth, and further researches are still needed in some particular contents. For instance, a simple and effective calculation method as well as the way to resolve the stochastic demand, time windows and unpredicted conditions. According to the relevant existing reports, based on the systematic ideology of modern logistics,abstracted actual problem from the post logistics practice,this dissertation constructs the mathematical models including post VRP with hard time windows, multi-objective post logistics mixed VRP and dynamic post logistics mixed VRP with soft time windows. The multi-objective genetic algorithm and adaptive polymorphic ant colony algorithm are designed, and have been presented for the solution to the post logistics VRP by taking YaFang integrated post with logistics delivery services in 11 cities in May 2008 by Sichuan post as the example. The optimal strategies also have been raised. Further analysis about implications on post freight costs and vehicle numbers in use under different optimal strategies also has been done.
     The main contents of this dissertation are listed as the following.
     In chapter1, the literature and theoretical achievements of post network, post logistics, domestic and foreign research achievements on VRP and algorithms have been summarized and sort out. The main research content and technological practices have been presented, based on the analysis of the latent fields of the multi-restricted conditions and multi-objective post logistics VRP.
     Chapter 2 is concentrated on the analysis of post transportation problem. The characteristic, classification and main influencing factors have been described for post transportation. The influence of transportation and delivery on post distribution press has also been analyzed. The monthly practical freight cost also has been calculated by taking Sichuan post in 11 cities as an example. The general model has also been put forward.
     In chapter 3, the model of post VRP with time windows has been constructed based on the analysis of restricted conditions like time windows and round-trip collection. The multi-objective genetic algorithm is designed to solute the post VRP with time windows in comparative analysis of post route optimization in 11 city post offices of Sichuan province. The influence of uncontrollable factors, such as emergency and earthquake, on post VRP also has been analyzed.
     In chapter 4, according to the characteristics of post logistic services, the vehicle scheduling and routing optimization problem has been analyzed on basis of the post transportation as well as the integration post logistical project. The adaptive polymorphic ant colony algorithm has been used to solve the multi-objective post logistic mixed VRP by which takes YaFang integrated post with logistics services in May 2008 by Sichuan post as an example. The influence of different type postal matter on post logistic mixed VRP also has been analyzed.
     In chapter 5, the model of minimum freight cost with time windows penalty has been built for the dynamic post logistic mixed VRP with soft time windows. It has been computed and comparatively analyzed by using of genetic algorithm, which takes care of the restrict conditions such as vehicle loading capacity, time windows, round-trip collection, mixed loading, time windows penalty and so on.
     In chapter 6, this dissertation comparatively analyses the total freight cost, vehicle numbers and optimal strategies, based on the theories, the post actual transportation problem, post VRP with time windows, multi-objective post logistic mixed VRP and dynamic post logistic mixed VRP through practical examples. Four optimal measures with practice have also been submitted.
     To sum up, the conclusion points out the main innovation of this dissertation and prospect the future research direction, which may be focused on the problem of post logistic mixed loading with multi-variety, multi-priority and multi-time limited.
引文
[1]Dantzig,G.The truck dispatching problem[J].Management Science.1959,12(1):80-91.
    [2]Lin,S.Computer solutions of the traveling salesman problem[J].Bell System Tech.1964:2245-2246.
    [3]Clarke,G.,Wright,R.Scheduling of Vehicles from a Central Depot to a Number of Delivery Points[J].Operations Research.1964,12:568-581.
    [4]Wilson,J.,Sussman,H.,Higgonet,B.Scheduling Algorithms for a Dial-A-Ride System[J].Cambridge,MA:Massachusetts Institute of Technology,Urban Systems Laboratory.1971(8):13-17.
    [5]Slin,B.,Kernighan,W.An effective heuristic algorithmfor the traveling salesman problem[J].Operations Research.1973(21):498-516.
    [6]Billy,E.,Gillett,L.A heuristic algorithm for vehicle dispatch problem[J].Operations Research.1974(22):340-349.
    [7]Netwon,R.Thomas,W.,Bus routing in a multi-school system[J].Computers and Operations Research.1974,1(1):213-222.
    [8]Chisman,A.The clustered traveling salesman problem[J].Computer Operation Research.1975(2):115-119.
    [9]Christodes,N.Worst-case analysis of a new heuristic for the traveling salesman problem[D].Pittsburgh,PA:Carnegie-Mellon University,1976.
    [10]Cornuejols,G.Tight bounds for christo_des traveling salesman heuristic[J].Math.Programming.1978(14):116-121.
    [11]Lokin,F.Procedures for the traveling salesman problem with additional constraints[J].Operations Research.1978(3):135-141.
    [12]Stern,H,Dror,M.Routing electric meter readers[J].Computers and Operations Research.1979,1(9):209-223.
    [13]goldon,B.,Lbodin,T.Approximate traveling salesman algorithms[J].Operations Research.1980,1(28):694-711.
    [14]Berman,L.Routing and scheduling of the vehicle routing and scheduling[J]. Networks. 1981, 1(11): 97-108.
    [15] Fisher, M. A generalized assignment heuristic for vehicle routing[J]. Networks. 1981, 1(11): 109—124.
    [16] Papadimitriou,K. Combinatorial Optimization: Algorithms and Complexity[J]. Control Engineering Practice. 1982.
    [17] Roundy,K. Effective Integer-Ratio Lot-Sizing for One-Warehouse Multi-Retailer System[J]. Management Science. 1985, 31(11): 1416-1429.
    [18] Jaillet,P. Probabilistic Traveling Salesman Problems. Ph.D. Thesis,[D]. Massachusetts Institute of Technology,USA, 1985.
    [19] Daganzo,F. Supplying a Single Location from heterogeneous Sources[J]. Transportation Science. 1985(27): 330-340.
    [20] Yao,D. Refining the Diffusion Approximations for the M/G/m Queue[J]. Operations Research. 1985(33): 1266-1277.
    [21] Solomon,M. Algorithms for the vehicle routing and scheduling problems with time window constraints[J]. Operations Research. 1987, 35(2): 254-265.
    [22] Larson,R. Transporting sludge to the 106-mile site: an inventory routing model for fleet sizing and component[J]. Large Scale System. 1988(22): 186-198.
    [23] Psaraftis,H. Vchicle Routing: Methods and Studies[M]. Amstersam North-Holland, 1988: 223-248.
    [24] Christodes, W. Vehicle scheduling problems with uncertainty and omitted customers[J]. Journal of the Operational Research Society. 1989, 40(05): 1099-1108.
    [25] Chien,T., Balakrishnan, A, Wong R T. An Integrated Inventory Allocation and Vehicle Routing Problem[J]. Transportation Science. 1989, 23(2): 67-76.
    [26] Anily,F. A Class of Euclidean Routing Problems with General Route Cost Function[J]. Mathematics of Operations Research. 1990, 15(2): 268-285.
    [27] Shoshana,F. One Warehouse Multiple Retailer Systems with Vehicle Routing Costs[J]. Management Science. 1990,36(1): 92-114.
    [28] Hoogeveen,A. Analysis of Christodes heuristic: Some paths are more di_cult than cycles[J]. Operations Research Letters. 1991(10): 291-295.
    [29] Mgendreau,L. New insertion and post-optimization procedures for the traveling salesman problem[J]. Operations Research. 1992, 1(40): 1086-1094.
    [30]Anily,F.Two-Echelon Distribution Systems with Vehicle Routing Costs and Central Inventories[J].Operation Research.1993,41(1):37-47.
    [31]Taillard,E.Parallel Iterative Search Methods for Vehicle Routing Problems[J].Networks.1993,1(23):661-673.
    [32]Glover,F.Tabu Search Modern heuristic Technique for Combinational Problems[M].Blackwell Scientific Publications,Oxford,1993:70-150.
    [33]Bertsimas,D.,Howell L.Further Results on the Probabilistic Traveling Salesman Problem[J].European Journal of Operational Research.1993(65):68-95.
    [34]Minkoff,S.Markov decision model and decom-position heuristic for dynamics vehicle dispatching[J].Operations Research.1993(41):77-90.
    [35]Henriksson,L.,Chowg,H.Trends in Logistics:Implication for Carriers,Researchers and Policymakers[C].1994.
    [36]Laporte,G.,Louveaux,F.A priori optimization of the probabilistic traveling salesman problem[J].Operations Research.1994,42(3):543-549.
    [37]Arkin,E.,Hassin,K.Restricted delivery problems on a network[J].Networks.1994(29):205-216.
    [38]Gendreau,M.,A.Hertz,G.Laporte.A Tabu Search Heuristic for the Vehicle Routing Problem[J].Management Science.1994,1(40):1276-1290.
    [39]Potvin,J.,Rousseau,J.An exchange heuristic for routing problems with time windows[J].Journal of the Operational Research Society.1995,46(12):1433-1466.
    [40]Bertsimas,D.,Chervi,P.,Peterson,M.Computational Approaches to Stochastic Vehicle Routing Problems[J].Transportation.Science.1995(29):342-352.
    [41]Shen,Y.,Potvin,J.,Yousseau,A.A computer assistant for vehicle dispatching with learning capability[J].Annals of Operations Research.1995(61):189-221.
    [42]郭耀煌,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(4):376-382.
    [43]Powell,W.Stochastic and dynamic networks and routing[M],master dam:North-Holland,1995:141-295.
    [44]Psaraftis,H.Dynamic vehicle routing:status and propects[J].Operations Research. 1995(61): 143-164. [45] Peter,M.,Bertsimas,R. Models and algorithms for transient queueing congestion at airports[J]. Management Science. 1995(41): 1279-1295.
    [46] Gambardella,M. Solving symmetric and asymmetric TSPs by ant colonies[J]. Proceedings of IEEE International Conference on Evolutionary Computation. 1996, IEEE - EC 96: 622-627.
    [47] Gendreau, M.,Laporte,G. Heuristic for the clustered traveling salesman probIem[J]. Combin. Optimization. 1996(1): 41-56.
    [48] Potivn,J. Genetic Algorithms for the Traveling Salesman Problem[J]. Operations Research. 1996(63): 339-370.
    [49] Bertsimas,S. A new generation of ve-hicle routing: robust algorithms, addressing uncertainty[J]. Operations Research. 1996(44): 286-304.
    [50] Dorigo,M. Ant colonies for the traveling salesman problem[J]. BioSystems. 1997, 43(2): 73-81.
    [51] Johnson,A. The travelling salesman problem: a case study in local optimization. in Local Search in Combinatorial Optimization[M]. Eds Aarts, Lenstra,K. New York : Wiley and Sons, 1997.
    [52] Philippe,G. A parallel tabu search heuristic for the vehicle routing problem with time window[J]. Transportation Research Part C. 1997, 5(2): 109-122.
    [53] Gendreau, M.,Hertz,G. An approximation algorithm for the traveling salesman problem with backhauls[J]. Operation Research. 1997(45): 639-641.
    [54] Guttman-beck,N.,Hassin, R. Approximation algorithms with bounded performance guarantees for the clustered traveling salesman problem[R]. Department of Statistics and Operations Research, Tel-Aviv University, 1997.
    [55] Gambardella, M. Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem[J]. IEEE Transactions on Evolutionary Computations. 1997, 1(1): 53-66.
    [56] Shaw,P. Using constraint programming and local warch methods to solve vehicle routing problem[C]. 1998.
    [57] Hostsa,H. Improvements on the Ant System: Introducing the MAX- MIN Ant System[J]. Artificial Neural Networks and Genetic Algorithms. 1998(3): 245-249.
    [58] Gendreau,J. Dynamic vehicle routing and dispatching[M]. Boston: KluwerAcademic Publishers,1998:115-127.
    [59]Martello,S.Voss,S.Meta-heuristics:Advances and Trends in Local Search Paradigms for Optimization[M].kluwer,boston,1999.
    [60]李大卫,王莉,王梦光.遗传算法在有时间窗车辆路径问题上的应用[J].系统工程理论与实践1999,19(8):65-69.
    [61]Cook,W.A parallel cutting plane algorithm of the vehicle muting problem with time windows[R].Rate University,1999.
    [62]马良,蒋馥.多目标旅行售货员问题的蚂蚁算法求解[J].系统工程理论方法应用.1999,8(4):23-27.
    [63]李军.车辆路径问题的分派启发式算法[J].系统工程理论与实践.1999,19(1):27-33.
    [64]李军.有时间窗的车辆调度问题的网络启发式算法[J].系统工程.1999(17):66-71.
    [65]谢秉磊,李军.遗传算法在非满载车辆线路安排问题中的应用[J].中国学术期刊文摘.1999,5(8):1068-1069.
    [66]Taillard,E.A heuristic column generation method for hetero-geneous fleet:[J].Research In Engineering Design-Theory Applications And Concurrent Engineering.1999,1(33):1-14.
    [67]邢文训,谢金星.现代优化计算方法[M].清华大学出版社,1999.
    [68]Dorigo,G.Gambardella LM.Ant Algorithms for Discrete Optimization[J].Artificial Life.1999,5(2):137-172.
    [69]陈龙,王国胤,刘心松等.一种启发式邮政运输调度优化方法[J].电子学报.2000,28(8):39-42.
    [70]Gambardella,M.An ant colony system hybridized with a new local search for the sequential ordering problem[J].INFORMS Journal on Computing.2000,12(3):237-255.
    [71]Kimjaegon,D.Simulated annealing algorithms for locating pickup and delivery points in an automated guided vehicle system[J].Journal of Engineering Valuation and Cost Analysis.2000,3(4):205-215.
    [72]谢秉磊,李军.多重旅行商问题的k-交换遗传算法[J].计算机应用研究.2000,17(增刊):1-2.
    [73]李军,谢秉磊.非满载车辆调度问题的遗传算法[J].系统工程理论方法应用.2000,9(3):235-239.
    [74]玄光男,程润伟.遗传算法与工程设计[M].北京:科学出版社,2000.
    [75]Dejun,H.Dynamic Routing Problem with Service Time Windows[M].香港:香港科技大学,2000.
    [76]杨伟,何义功,杜文.邮运汽车套班的计算机编排算法研究[J].西南交通大学学报.2001,36(4):407-411.
    [77]Cordeau,L.A unified tabu search heuristic for vehicle routing problems with time windows[J].Journal of the Operational Research Society.2001,52(8):928-936.
    [78]Cordeau,G.A tabu search algorithm for the site dependent vehicle routing problem with time windows[J].INFOR Journa.2001,39(3):292-298.
    [79]Kalehauge,B.,Larien,J.Lagrangean duality applied on vehicle routing with time windows[R].IMM-TR,2001.
    [80]张丽萍,柴跃廷.遗传算法的现状及发展动向[J].信息与控制.2001,30(12):531-535.
    [81]李军,郭耀煌.物流配送车辆优化调度理论与方法[M].中国物资出版社,2001.
    [82]马良,项培军.蚂蚁算法在组合优化中的应用[J].管理科学学报.2001,4(2):32-37.
    [83]李军,郭强,刘建新.组合运输的优化调度[J].系统工程理论与实践.2001,21(2):117-121.
    [84]Tanklee,A.A messy genetic algorithm for the vehicle routing problem with dme window constraints[C].2001.
    [85]吴斌,史忠植.一种基于蚁群算法的TSP问题分段求解算法[J].计算机学报.2001,24(12):1328-1333.
    [86]Xiangwen,L.Dynamic and Stochastic Routing Optimization:Algorithms[J].Development and Analysis.2001(3):12-18.
    [87]Paolo,V.The vehicle problem[M].Society for Industry and Applied Mathematics,2002:158-160.
    [88]Bianchi L,gambardella L M D M.An ant colony optimization approach to the probabilistic traveling salesman problem[C].Berlin,Germany:2002.
    [89]St(u|¨)tzle,T.,Dorigo,M.A short convergence proof for a class of ACO algorithms[J].IEEE Transactions on Evolutionary Computation.2002,6(4):358-365.
    [90]Christofides,D.Dynamic,A.Armaou optimization of dissipative PDE systems using nonlinear order reduction[J].Chemical Engineering Science.2002(57):5083-5114.
    [91]Reimann,K.,Mdorener,F.Insertion based ants for vehicle routing problems with backhauls and time windows[M].Berlin Germany:2002:135-147.
    [92]张丽萍,柴跃廷,曹瑞.有时间窗车辆路径问题的改进遗传算法[J].计算机集成制造系统.2002,8(6):451-454.
    [93]袁健,刘晋,卢厚清.随机需求情形VRP的退火网络解法[J].系统工程理论与实践.2002,22(3):109-113.
    [94]谢秉磊,郭耀煌,郭强.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(2):116-120.
    [95]冯祖洪,徐宗,.用混合型蚂蚁群算法求解TSP问题[J].工程数学学报.2002,19(4):35-39.
    [96]郭冬芬,何东彬.GIS在邮政物流配送管理信息系统中的应用[J].邮政研究.2002,18(6):28-30.
    [97]郎茂祥.物流配送车辆调度问题的模型和算法研究[D].北京:北方交通大学,2002.
    [98]袁庆达.随机库存-运输联合优化问题研究[D].成都:西南交通大学,2002
    [99]Solomon,C.Ants Can Solve Constraint Satisfaction Problems[J].Transactions on Evolutionary Computation.2002,6(4):347-357.
    [100]Adelman,D.Price-Directed Replenishment of Subsets:Methodology and its Application to Inventory Routing[J].Manufacturing & Service Operations Management.2003,5(4):348-371.
    [101]Luci,P.Vehicle routing problem with uncertain demand at nodes:The bee system and fuzzy logic approach[C].2003.
    [102]秦淑芬.中国邮政物流的发展战略[D].2003.
    [103]姜世锋.库存路线问题[D].西南交通大学硕士论文,2003.
    [104]谢秉磊.随机车辆路径问题研究[D].西南交通大学博士论文,2003.
    [105]张建勇,郭耀煌,李军.基于顾客满意度的多目标模糊车辆优化调度问题研究[J].铁道学报.2003,25(2):281-284.
    [106]陈崚,秦玲陈宏建,徐晓华.具有感觉和知觉特征的蚁群算法[J].系统仿真学报.2003,15(10):1418-1425.
    [107]Baker,M.A genetic algorithm for the vehicle routing problem[J].Computers Operations Research.2003,30(2):787-800.
    [108]郭耀煌,谢秉磊.一类随机动态车辆路径问题的策略分析[J].管理工程学报.2003(4):114-115.
    [109]Alvarenga,R.A two-phase genetic and set partitioning approach for the vehicle routing problem with time windows[C].2004.
    [110]Dorigo,T.Ant colony optimization[M].Berlin Germany:2004:161-167.
    [111]Sorensen,K.Robust and flexible vehicle routing in practicaal situations[M].France:Proceedings of the 5th Triennial Symposium on Transportation Analysis,2004.
    [112]Berger,J.A parallel hybrid genetic algorithm for the vehicle routing problem with time windows[J].Computers and Operations Research.2004,31(12):2037-2053.
    [113]John,E.,Patrick,R.Ant colony optimization techniques for the vehicle routing problem[J].Advanced Engineering Informatics.2004(18):41-48.
    [114]宝勒德.我国邮政物流业发展战略研究[D].2004.
    [115]吕维平,王莉媛.中国农村邮政物流SWOT分析与发展对策[C].2004.
    [116]张建勇.模糊信息条件下车辆路径问题研究[D].西南交通大学博士论文,2004.
    [117]李军,刘建新.第三方存贮-路径问题研究综述[J].科学技术与工程.2004,4(4):325-328.
    [118]崔雪丽,马良,范炳全.车辆路径问题(VRP)的蚂蚁搜索算法[J].系统工程学报.2004,19(4):418-422.
    [119]肖增敏,李军.动态网络车辆路径问题:研究现状及展望[J].系统工程.2004(7):68-71.
    [120]Tang,H.And Miller-hooks E.Approximate Procedures for the Probabilistic Traveling Salesperson Problem[C].2004.
    [121]Branke,J.,Guntsch,M.Solving the Probabilistic TSP with Ant Colony Optimization[J].Mathematical Modeling and Algorithms.2004(3):403-425.
    [122]Leonora,B.,Chiarandinic,A.Hybrid metaheuristics for the vehicle routing problem with stochastic demands[M].IDSIA,2005:06-05.
    [123]刘毅松,孙雨耕,胡华东.超限车辆的最短路径在MAPGIS中的实现[J].计算机工程与设计.2005,26(9):2335-2337.
    [124]刘云忠,宣慧玉.动态蚁群算法在带时间窗车辆路径问题中的应用[J].中国工程科学.2005(12):39-44.
    [125]柳键.基于时变需求的供应链库存决策研究[M].中国科学技术大学出版社,2005.
    [126]段海滨.蚁群算法原理及其应用[M].北京:科学出版社,2005.
    [127]张茹秀.库存-运输联合优化问题[D].大连:大连海事大学,2005.
    [128]刘兴,贺国光,高文伟.一种有时间约束的多车辆协作路径模型及算法[J].系统工程.2005(4):105-109.
    [129]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(1):124-130.
    [130]Bianchi,L.,Knowles,J.And Bowler N.Local Search for the Probabilistic Traveling Salesman Problem:Correction to The 2p-opt and 1-shift Algorithms[J].Operations Research.2005(162):206-219.
    [131]Montemanni,R.,Gambardella,A.Ant Colony System for a Dynamic Vehicle Routing Problem[J].Combinatorial Optimization.2005,10(4):327-343.
    [132]Oliveira,H.,Bvasconelos,G.Reducing traveled distance in the vehicle routing problem with time windows using a multi-start simulated annealing[C].2006.
    [133]李莉.吉林邮政发展现代物流策略研究[D].2006.
    [134]李全亮.蚂蚁算法在带时间窗车辆路径问题中的应用研究[J].数学的实践与认识.2006,36(10):173-178.
    [135]唐勇,刘峰涛.新型遗传模拟退火算法求解VRPTW问题[J].计算机工程与应用.2006(7):7-9.
    [136]丁秋雷.带有时间窗的车辆路径问题的混合蚁群算法研究[D].大连理工大学,2006.
    [137]孙曦.带时间窗的车辆路径规划问题的遗传算法研究[D].北京:清华大学,2006.
    [138]张力波,陈杰,马义中.基于时间的VMI整合补货模式的系统成本与牛鞭效应[J].系统工程.2006,24(10):26-33.
    [139]于春云,赵,南,彭艳东.模糊随机需求模式下的扩展报童模型与求解算法[J].系统工程.2006,24(9):103-107.
    [140]李勇,叶世杰,王勇.VFP&VRP联合优化模型及其多目标遗传算法[J].系统工程学报.2006,21(5):529-533.
    [141]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(11):31-35.
    [142]吴守辉.中邮物流公司业务流程优化研究[D].长春:吉林大学,2006.
    [143]夏国成,赵佳宝.智能蚂蚁算法求解多目标TSP问题的改进研究[J].计算机工程与应用.2006,42(6):56-59.
    [144]柳林,朱建荣.基于混合蚂蚁算法的物流配送路径优化问题研究[J].计算机工程与应用.2006,42(13):203-205.
    [145]沈垚.基于改进蚁群算法的配送路线优化研究[D].南京:东南大学,2006.
    [146]郭耀煌,钟小鹏.动态车辆路径问题排队模型分析[J].管理科学学报.2006(1):33-37.
    [147]张杨,黄庆,卜祥智.随机旅行时间局内车辆路径问题的模型及其算法[J].管理工程学报.2006(3):82-84.
    [148]Liu,Y.A Scatter Search Based Approach with Approximation Evaluation for the Heterogeneous Probabilistic Traveling Salesman Problem[C].Vancouver,Canada:2006.
    [149]郝光,张殿业,冯勋省.多目标最短路径模型及算法[J].西南交通大学学报.2007,42(5):641-646.
    [150]朱晨波,叶耀华,戴锡.直接配送的三层随机库存路径问题[J].系统工程理论与实践.2007(12):16-22.
    [151]魏航,李军,魏洁.时变条件下多式联运有害物品的路径选择[J].系统管理学报.2007,16(6):644-652.
    [152]邓玉芬,向凤红.蚁群算法在组合优化中的应用[J].电子测量技术.2007(1):38-41.
    [153]秦进,史峰,裴军.考虑库存控制的物流网络设计优化模型与算法[J].系统工程.2007,25(12):24-29.
    [154]张涛,王珊珊,田文馨.车辆可重复利用VRPTW问题的模型和改进蚁群算法[J].系统工程.2007,25(4):21-26.
    [155]蒋琦玮,陈治亚.物流配送最短路径的动态规划方法研究[J].系统工程.2007,25(4):27-29.
    [156]赵达,李军,李妍峰.随机需求库存-路径问题:研究现状及展望[J].系统工程.2007,25(8):38-44.
    [157]杨阳,刘志学.供应商管理库存与第三方物流的系统动力学模型[J].系 统工程.2007,25(7):38-44.
    [158]高峻峻,胡乐江.模糊环境下分销系统的库存决策问题研究[J].系统工程学报.2007,22(4):407-411.
    [159]肖峰.邮政车辆调度问题研究[D].昆明:昆明理工大学,2007.
    [160]邱平.车辆路径问题研究[D].大连:大连海事大学,2007.
    [161]谢苏苏.一类智能算法在物流运输-库存联合优化问题中的应用研究[D].南京:南京理工大学,2007.
    [162]孙学农.遗传算法在非满载车辆调度中的应用研究[D].中国石油大学,2007.
    [163]高雷阜,张晓翠.基于最大最小蚂蚁系统的物流配送中心选址算法的研究[J].运筹与管理.2007,16(6):42-46.
    [164]崔雪丽,马良.多目标0-1规划的蚂蚁优化算法[J].计算机应用与软件.2007,24(7):23-24.
    [165]朱刚,马良.TSP的元胞蚁群算法求解[J].计算机工程与应用.2007,43(10):79-80.
    [166]胡红春,吴耀华,廖莉.物流配送车辆线路的优化及其应用[J].山东大学学报:工学版.2007(4):104-107.
    [167]钟石泉,杜纲,贺国光.有顾客时间窗和发货量变化的紧急车辆调度研究[J].管理工程学报.2007(4):114-118.
    [168]Yihou,L.,Ruchou,J.An Evolutionary Algorithm with Diversified Crossover Operator for the Heterogeneous Probabilistic TSP[C].Kitakyushu,Japan:2007.
    [169]Qinhai,Z.,Siyang,W.A Parition Approach To The Inventory/Routing Problem[J].European Journal Of Operational Research.2007,177(2):786-802.
    [170]高玉建,苏昊,黄飞.邮政运输网络中的邮路规划和邮车调整[J].数学的实践与认识.2008,38(14):173-178.
    [171]马良,朱刚,宁爱兵.蚁群优化算法[M].科学出版社,2008.
    [172]黄樟灿,蒋文霞,李书琻.有时间窗车辆路径问题的混合算法[J].武汉理工大学学报.信息与管理工程版.2008(1):48-51.
    [173]尹影影,唐兵.蚁群算法在网格资源调度中的应用[J].武汉理工大学学报.信息与管理工程版.2008(1):35-38.
    [174]张建勇,李军,郭耀煌.带模糊预约时间的动态VRP的插入启发式算法[J].西南交通大学学报.2008,43(1):107-113.
    [175]王有为.基于禁忌表的捕食搜索算法及其在旅行商问题中的实验研究[J].系统工程理论与实践.2008(2):131-136.
    [176]张涛,田文馨,张玥杰.带车辆行程约束的VRPSD问题的改进蚁群算法[J].系统工程理论与实践.2008(1):132-140.
    [177]王红蕾,俞建.有限理性与多目标问题解的稳定性[J].运筹学学报.2008,12(1):104-108.
    [178]陈美军,张志胜,史金飞.基于自适应多态蚁群算法的多约束车辆路径问题[J].东南大学学报.2008,38(1):37-42.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700