物流配送系统需求量变动的干扰管理模型研究
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摘要
物流配送是企业对顾客服务的最后一个环节,如何为客户提供及时而满意的配送服务,是物流配送运营商必须解决的重要问题。在实际的物流配送过程中,经常会受到某些随机事件的干扰,如客户需求量变动、客户时间窗变动、车辆故障等,使已有的配送计划变得不可行,无法满足客户的需求以致客户满意度大幅下降。如何有效地处理干扰事件,使得对整个物流配送系统产生的扰动最小,已成为物流配送管理中的难点问题。
干扰管理(Disruption Management)作为一种实时处理干扰事件的方法论,主要针对经常性干扰事件的处理和管理。它根据各种实际问题和干扰事件的性质,建立相应的优化模型和有效的求解算法,及时生成最优的调整方案。该调整方案既要满足新目标与新约束,又要达到多方满意,使其对物流配送系统的扰动最小。本文运用干扰管理的方法,对物流配送中发生频率极高的客户需求量变动问题展开了研究,主要研究工作如下:
(1)在分析物流配送需求量变动的干扰问题的基础上,提出了扰动辨识的方法;从客户,车辆驾驶员和物流配送运营商三个主体的角度研究了干扰事件的扰动因素,建立了相关因素的扰动度量函数;根据不同物流运营商的经营目标,给出了不同的系统客户不满意度的衡量准则。
(2)以带有时间窗的可拆分的车辆路径问题(Split Delivery Vehicle RoutingProblem with Time Windows,SDVRPTW)为研究背景,构建了物流配送需求量变动的干扰管理模型。
(3)研究并设计了基于禁忌搜索算法(Tabu Search Algorithm)和插入算法(Inserting Algorithm)的混合启发式算法,用于求解物流配送需求量变动的干扰管理模型,实现快速实时生成物流配送需求量变动问题的干扰管理调整方案。
(4)用算例验证了物流配送需求量变动的干扰管理模型以及求解算法的有效性。
本文构建的需求量变动的干扰管理模型,可以克服传统的优化方法事前性和全局优化的缺陷,有效降低干扰事件给物流配送系统带来的扰动,能够大大减小了客户不满意度和成本的损失,为物流配送系统干扰管理提供新的思路。
Distribution is the last task when a company services customers. How to deliver the right products to customers at right time is the most important problem for distribution companies which focus on Milling customer satisfaction. In practice, there are numerous uncertainties such as changes in customer demand, changes in service time windows, vehicle breakdowns and so on which disable the initial distribution plan, leading to decreasing customer satisfactions. The way how to deal with disruption events effectively, which minimize disturbance resulting from disruption happening in distribution system, is the difficult problem in urban distribution management.
Disruption management is a methodology that resolves this kind of problems in real-time. It is a multi-objective decision-making method that a new distribution plan should fulfill new goals and new constraints, as well as minimize the deviations from the original plan and achieve multi-party satisfaction when disruption events appear. This paper applies disruption management to demand changing problem which happens frequently in distribution system. The main researches are as follows:
(1) On the basis of analyzing customer demand changing problem, the paper proposed the method of disturbance identification, researching on disturbance factors from the three actors of customers, drivers and distribution operators and constructed disturbance measurement function. Different criteria to measure systematic dissatisfactions are investigated according to operational goals in different distribution companies.
(2)Based on Split Delivery Vehicle Routing Problem with Time Windows, using the methods of measuring disturbance, a disruption management model for demand changing in distribution system is constructed.
(3)Hybrid heuristic combined Tabu Search algorithm and Inserting algorithm to solve model is designed. When a disruption event appears, the initial distribution plan is optimized in real-time.
(4)Applying the model and algorithm to a case, the result shows that the proposed model and algorithm are feasible and effective.
The presented disruption management model for demand changing in distribution system is proved to be efficient in minimizing the impacts of disruption events. It reduces customer dissatisfactions and the rise of costs.
干扰管理(Disruption Management)作为一种实时处理干扰事件的方法论,主要针对经常性干扰事件的处理和管理。它根据各种实际问题和干扰事件的性质,建立相应的优化模型和有效的求解算法,及时生成最优的调整方案。该调整方案既要满足新目标与新约束,又要达到多方满意,使其对物流配送系统的扰动最小。本文运用干扰管理的方法,对物流配送中发生频率极高的客户需求量变动问题展开了研究,主要研究工作如下:
(1)在分析物流配送需求量变动的干扰问题的基础上,提出了扰动辨识的方法;从客户,车辆驾驶员和物流配送运营商三个主体的角度研究了干扰事件的扰动因素,建立了相关因素的扰动度量函数;根据不同物流运营商的经营目标,给出了不同的系统客户不满意度的衡量准则。
(2)以带有时间窗的可拆分的车辆路径问题(Split Delivery Vehicle RoutingProblem with Time Windows,SDVRPTW)为研究背景,构建了物流配送需求量变动的干扰管理模型。
(3)研究并设计了基于禁忌搜索算法(Tabu Search Algorithm)和插入算法(Inserting Algorithm)的混合启发式算法,用于求解物流配送需求量变动的干扰管理模型,实现快速实时生成物流配送需求量变动问题的干扰管理调整方案。
(4)用算例验证了物流配送需求量变动的干扰管理模型以及求解算法的有效性。
本文构建的需求量变动的干扰管理模型,可以克服传统的优化方法事前性和全局优化的缺陷,有效降低干扰事件给物流配送系统带来的扰动,能够大大减小了客户不满意度和成本的损失,为物流配送系统干扰管理提供新的思路。
Distribution is the last task when a company services customers. How to deliver the right products to customers at right time is the most important problem for distribution companies which focus on Milling customer satisfaction. In practice, there are numerous uncertainties such as changes in customer demand, changes in service time windows, vehicle breakdowns and so on which disable the initial distribution plan, leading to decreasing customer satisfactions. The way how to deal with disruption events effectively, which minimize disturbance resulting from disruption happening in distribution system, is the difficult problem in urban distribution management.
Disruption management is a methodology that resolves this kind of problems in real-time. It is a multi-objective decision-making method that a new distribution plan should fulfill new goals and new constraints, as well as minimize the deviations from the original plan and achieve multi-party satisfaction when disruption events appear. This paper applies disruption management to demand changing problem which happens frequently in distribution system. The main researches are as follows:
(1) On the basis of analyzing customer demand changing problem, the paper proposed the method of disturbance identification, researching on disturbance factors from the three actors of customers, drivers and distribution operators and constructed disturbance measurement function. Different criteria to measure systematic dissatisfactions are investigated according to operational goals in different distribution companies.
(2)Based on Split Delivery Vehicle Routing Problem with Time Windows, using the methods of measuring disturbance, a disruption management model for demand changing in distribution system is constructed.
(3)Hybrid heuristic combined Tabu Search algorithm and Inserting algorithm to solve model is designed. When a disruption event appears, the initial distribution plan is optimized in real-time.
(4)Applying the model and algorithm to a case, the result shows that the proposed model and algorithm are feasible and effective.
The presented disruption management model for demand changing in distribution system is proved to be efficient in minimizing the impacts of disruption events. It reduces customer dissatisfactions and the rise of costs.
引文
[1]Gang Yu,Xiangtong Qi.Disruption management:framework,models and applications[M].Singapore:World Scientific Publishing Co.Pte.Ltd.,2004.
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[2]BERTSIMAS D.Probabilistic combinatorial optimization problems[D].Operation Research Center,Massachusetts Institute of Technology,Cambridge,MA 1988.
[3]GENDREAU M,LAPORTE G,SEGUIN R.Stochastic vehicle routing[J].European Journal of Operational Research,1996,88(1):3-12.
[4]STEWART W,GOLDEN B.Stochastic vehicle routing:a comprehensive approach[J].European Journal of Operational Research,1983,14(4):371-385
[5]BERTSIMAS D.Probabilistic combinatorial optimization problems[D].Operation Research Center,Massachusetts Institute of Technology,Cambridge,MA 1988.
[6]TILLMAN F.The multiple terminal delivery problem with probabilistic demands[J].Transportation Science,1969,3(3):192-204.
[7]LAPORTE G,LOUVEAUX F,MERCURE H.Models and exact solutions for a class of stochastic location-routing problems[J].European Journal of Operational Research,1989,39(1):71-78.
[8]SEGUIN R.Problems stochastiques de vehicles[D].Centre de Reserche Sur Les Transports,University de Montreal,1994.
[9]GENDREAUM,LAPORTEG,SEGUINR.An exact algorithm for the vehicle routing problem with stochastic customers and demands[J].Transportation Science,1995,29(2):143-155.
[10]王德东,郑丕谔.供应链中随机需求车辆选径问题的研究[J].工业工程,2006,9(5):97-100.
[11]JEZEQUEL A.Probabilistic vehicle routing problems[D].Department of Civil Engineering,Massachusetts Institute of Technology,Cambridge,MA 1985.
[12]JAILLETP,ODONI A.The probabilistic vehicle routing problem[A].GOLDEN BL.Vehicle routing Methods and Studies[C].Amsterdam:North Holland,1988.
[13]谢秉磊.随机车辆路径问题研究[D].成都:西南交通大学.2003.
[14]GENDREAR M,LAPORTE G,SEGUIN R.A tabu search heuristic for the vehicle routing problem with stochastic demand customers[J].Operations Research,1996,44(3):469-477.
[15]GLOVER F.Tabu search[A].REEVES C.Modem Heuristic Techniques for Combinational Optimization[C].Blackwell,Oxford,1993.
[16]Liu F.E,Shen S..Overview of a heuristic for vehicle routing problem with time windows.Computers and Industrial Engineering.1999,37(1):331-334
[17]GENDREAU M,LAPORTE G,SEGUINR.An exact algorithm for the vehicle routing problem with stochastic customers and demands[J].Transportation Science,1995,29(2):143-155.
[18]Teodorovic D.,Pavkovic G..The fuzzy set theory approach to the vehicle routing problem when demand at nodes is uncertain.[J]Fuzzy Set and Systems.1996,82:307-317
[19]Teodorovic D.,Radivojevic G..A fuzzy logic approach to dynamic Dial-A-Ride problem[J].Fuzzy Set and Systems.2000,116:23-33
[20]Chen R,Gen.M.Vehicle routing problem with fuzzy due-time using genetic algorithms[J].Japanese Journal of Fuzzy Theory and Systems,1995;7(5):1050 - 1061
[21]祝崇隽,刘民,吴澄.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(11):1-6.
[22]郭耀煌,李军著.车辆优化调度[M].成都:成都科技大学出版社,1994.
[23]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):15-17.
[24]Gillett B.,Miller L..A heuristic algorithm for the vehicle dispatch problem[J].Operations Research Quarterly.1976,27:367-384
[25]谢秉磊,郭耀煌,郭强.动态车辆路径问题:现状与展望.系统工程理论方法应用,2002,11(2):116-120.
[26]Jinyan SONG,Jianming HU,Yan TIAN etc.Re-optimization in Dynamic Vehicle Routing Problem Based on Wasp-like Agent Strategy.Proceedings of the 8~(th) International IEEE Conference on Intelligent Transportation Systems Vienna,Austria,September 13-16,2005.688-693.
[27]Rhalibi,E.A.,Kelleher,G.An Approach to Dynamic Vehicle Routing,Rescheduling and Disruption Metrics.IEEE International Conference on Systems,Man and Cybernetics 4,2003,3613-3618
[28]Mardsen O B G,Ravn H F,Voelds J.A heuristic method for dispatching repair men.Annals of Operations Research,1995,61:193-208.
[29]Gendreau M,Guerlin F,Polvin J Y,et al.Tahu search ror real-time vehicle routing and dispatching.Technical Report CRT96-47,Centre de Recherche Sur Les Transports,University de MonLreal,1996.
[30]Gendreau M,GuerLin F,Potvin J Y,et al.Parallel tahu search for real-time vehicle routing and dispatching.Transportation Science,1996,33:381-390.
[31]Psaraftis H.N..A Dynamic Programming Solution the Single Vehicle Many-to-Many Immediate Request DIAL-A-RIDE Problem.Transportation Science,1980(14):130-154.
[32]Clausen J,Jesper H,Jesper L,et al.Disruption Management.OR/MS Today,2001,28(5):40-43.
[33]陈安,李铭禄.干扰管理,危机管理和应急管理概念辨析[J].应急管理汇刊,Nov.8,2006,1(1):8-9.
[34]Balinski M,Quandt R.On an integer program for a delivery problem.Operations Research,1962,12:300-304.
[35]胡祥培,丁秋雷,张漪,王旭坪.干扰管理研究评述[J].管理科学,2007,20(2):2-8.
[36]王旭坪,傅克俊,胡祥培.应急物流系统及其快速反应机制研究[J].中国软科学,2005,(6):127-131.
[37]Yu G,Michael Arguelo,Gao S,Sandra M McCowan,Anna White.A new era for crew recovery at continental airlines[J].Interfaces,2003,33(1):5-22.
[38]Wu C L.Inherent delays and operational reliability of airline schedules[J].Elsevier Science,Journal of Air Transport Management,2005,(11):273-282.
[39]Xiangtong Qi,Jonathan F Bard,Gang Yu.Supply Chain Coordination with Demand Disruption[J].Omega,2004,32(4):301-312.
[40]于辉,陈剑,于刚.协调供应链如何应对突发事件[J].系统工程理论与实践,2005,(7):9-16.
[41]M A Al Fawzana,Mohamed Haouarib.A Bi-objective Model for Robust Resource-constrained Project Scheduling[J].International Journal of Production Economics,2005,96(2):175-187.
[42]Daesik Hur,Vincent A Mabertb,Kurt M Bretthauer.Real-time Schedule Adjustment Decisions:A Case Study[J].Omega,2004,32(5):333-344.
[43]Zhu Z,Bard J F,Yu G.Disruption Management for Resource-constrained Project Scheduling[J].Journal of the Operational Research Society,2005,56(4):365-381.
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