行驶受扰延迟下配送车辆调度的干扰管理决策模型
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摘要
针对行驶受扰延迟下配送车辆的调度问题,提出了基于多相量子粒子群算法的两阶段干扰管理决策方法.首先以最小化用户时间窗偏离度和最小化配送成本为目标,建立了问题的数学模型;然后对车辆配送发生干扰事件可能采取的干扰管理模式进行了归纳和分类,并在选定模式基础上提出了用多相量子粒子群算法进行路线选择的方法;最后在Solomon算例的基础上通过实验仿真,对所提出方法的性能进行测试,并与全局重调度方法进行对比分析,验证了本文方法不仅达到了优化目标的目的,还满足了干扰管理的实用性要求.
In order to solve the vehicle scheduling problem with traffic disruption delay, a two-stage disruption management method based on multi-phase quantum particle swarm optimization(MQPSO)is proposed. Firstly, a mathematical model of the problem is established to minimize the time window deviation and minimize the distribution cost. Next, the possible disruption management mode of distribution vehicles is summarized and classified and the route scheduling method is proposed on the basis of selected mode. At last, the simulation experiments are executed based on the Solomon example to test the performance of the proposed method. The effectiveness and practicability of the proposed method is verified through the comparison and analysis with rescheduling method.
In order to solve the vehicle scheduling problem with traffic disruption delay, a two-stage disruption management method based on multi-phase quantum particle swarm optimization(MQPSO)is proposed. Firstly, a mathematical model of the problem is established to minimize the time window deviation and minimize the distribution cost. Next, the possible disruption management mode of distribution vehicles is summarized and classified and the route scheduling method is proposed on the basis of selected mode. At last, the simulation experiments are executed based on the Solomon example to test the performance of the proposed method. The effectiveness and practicability of the proposed method is verified through the comparison and analysis with rescheduling method.
引文
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[17]赵锋,吴成茂.自编码和超混沌映射相结合的图像加密算法[J].计算机辅助设计与图形学学报,2016, 28(1):119-128.Zhao F, Wu C M. Image encryption algorithm combined self-encoded theory with super-chaotic mapping[J].Journal of Computer-Aided Design and Computer Graphics, 2016, 28(1):119-128.
[18] Solomon M. Solomon benchmark problems[EB/OL].[2009-2-28]. http://www.idsia.ch/luca/macs-vrptw/problems/welcome.htm.
[19] Do J Y, Kim D K. AHP-based evaluation model for optimal selection process of patching materials for concrete repair:Focused on quantitative requirements[J]. International Journal of Concrete Structures and Materials,2012, 6(2):87-100.
[20] Ning T, Jin H, Song X D, et al. An improved quantum genetic algorithm based on MAGTD for dynamic FJSP[J].Journal of Ambient Intelligence and Humanized Computing, 2018, 9(4):931-940.
[21] Shi B F, Meng B, Yang H F, et al. A novel approach for reducing attributes and its application to small enterprise financing ability evaluation[J]. Complexity, 2018, Article ID 1032643. http://doi.org/10.1155/2018/1032643.
[22] Sheng X Y, Xi M L, Sun J, et al. Quantum-behaved particle swarm optimization with novel adaptive strategies[J].Journal of Algorithm&Computational Technology, 2015, 9(2):143-162.
[23]阮俊虎,王旭坪.中转点变化的应急医疗物资联合运送千扰管理研究[J].运筹与管理,2016, 25(4):114-124.Ruan J H, Wang X P. Disruption management of emergency medical supplies intermodal transportation with updated transit centers[J]. Operations Research and Management Science, 2016, 25(4):114-124.
[2] Potvin J Y, Xu Y, Benyahia I. Vehicle routing and scheduling with dynamic travel times[J]. Computers&Operations Research, 2006, 33(4):1129-1137.
[3] Mohammad K, Mohammad A, Mutaz M A, et al. An adaptive decision support system for the last mile logistics in e-commerce:A study on online grocery shopping[J]. International Journal of Decision Support System Technology, 2013, 5(1):40-65.
[4] Gevaers R, Voorde E V de, Vanelslander T. Cost modeling and simulation of last-mile characteristics in an innovative B2C supply chain environment with implications on urban areas and cities[J]. Procedia Social and Behavioral Sciences, 2014, 125(20):398-411.
[5] Sasipriya S, Ravichandran C S. Performance analysis of overloaded CDMA system under imperfect synchronization using parallel/successive interference cancellation[J]. Telecommunication Systems, 2014, 56(4):509-518.
[6] Yap M D, Correia G, van Arem B. Preferences of travelers for using automated vehicles as last mile public transport of multimodal train trips[J]. Transportation Research Part A, 2016, 94:1—16.
[7]李琳,刘士新,唐加福.B2C环境下带信息流的多阶段订单配送问题[J].控制理论与应用,2010, 27(10):1293-1299.Li L, Liu S X, Tang J F. Multistage order-delivery problem with information flow under B2C environment[J].Control Theory and Application, 2010, 27(10):1293-1299.
[8]潘茜茜,千宏程.考虑碳排放的冷链物流配送路径优化研究[J].数学的实践与认识,2016, 46(2):62-68.Pan Q Q, Gan H C. Study on the optimization of cold chain logistics distribution path considering carbon emission[J]. Mathematics in Practice and Theory, 2016, 46(2):62-68.
[9]刘明,赵林度.应急物资混合协同配送模式研究[J].控制与决策,2011, 26(1):96-100.Liu M, Zhao L D. Mix-collaborative distribution mode of emergency materials[J]. Control and Decision, 2011,26(1):96-100.
[10]丁秋雷,胡祥培,姜洋,等.考虑客户消费行为的易逝品物流配送千扰管理模型[J].运筹与管理,2016, 25(6):68-74.Ding Q L, Hu X P, Jiang Y, et al. Model of disruption management with consumption behavior in logistic disruption of perishable goods[J]. Operations Research and Management Science, 2016, 25(6):68-74.
[11]王征,胡祥培,王旭坪.行驶时间延迟下配送车辆调度的千扰管理模型与算法[J].系统工程理论与实践,2013, 33(2):378-387.Wang Z, Hu X P, Wang X P. Disruption management model and algorithm for distribution vehicle scheduling problems under accidental travel time delay[J]. Systems Engineering—Theory&Practice, 2013, 33(2):378-387.
[12]宁涛,王旭坪,胡祥培,等.基于前景理论的物流配送千扰管理优化调度方法[J].控制与决策,2018, 33(11):2064-2068.Ning T, Wang X P, Hu X P, et al. Disruption management optimal scheduling for logistics distribution based on prospect theory[J]. Control and Decision, 2018, 33(11):2064-2068.
[13]李锐,黄敏,王兴伟.多周期的第四方物流弹复性正逆向集成网络设计模型与算法[J].系统工程理论与实践,2015, 35(4):892-903.Li R, Huang M, Wang X W. Model and algorithm for multi-period resilient integrated forward/reverse network design of fourth-party logistics[J]. Systems Engineering—Theory&Practice, 2015, 35(4):892-903.
[14]丁秋雷,姜洋,王文娟,等.鲜活农产品冷链物流配送的千扰管理模型研究[J].系统工程理论与实践,2017, 37(9):40-46.Ding Q L, Jiang Y, Wang W J, et al. Disruption management model for cold chain delivery of fresh agricultural products[J]. Systems Engineering—Theory&Practice, 2017, 37(9):40-46.
[15] Yu G, Qi X T. Disruption management:Framework, models and applications[M]. Singapore:World Scientific Publishing Co. Pte Ltd, 2004.
[16] Ning T, Huang M, Liang X, et al. A novel dynamic scheduling strategy for solving flexible job-shop problems[J].Journal of Ambient Intelligence&Humanized Computing, 2016, 7(5):1-9.
[17]赵锋,吴成茂.自编码和超混沌映射相结合的图像加密算法[J].计算机辅助设计与图形学学报,2016, 28(1):119-128.Zhao F, Wu C M. Image encryption algorithm combined self-encoded theory with super-chaotic mapping[J].Journal of Computer-Aided Design and Computer Graphics, 2016, 28(1):119-128.
[18] Solomon M. Solomon benchmark problems[EB/OL].[2009-2-28]. http://www.idsia.ch/luca/macs-vrptw/problems/welcome.htm.
[19] Do J Y, Kim D K. AHP-based evaluation model for optimal selection process of patching materials for concrete repair:Focused on quantitative requirements[J]. International Journal of Concrete Structures and Materials,2012, 6(2):87-100.
[20] Ning T, Jin H, Song X D, et al. An improved quantum genetic algorithm based on MAGTD for dynamic FJSP[J].Journal of Ambient Intelligence and Humanized Computing, 2018, 9(4):931-940.
[21] Shi B F, Meng B, Yang H F, et al. A novel approach for reducing attributes and its application to small enterprise financing ability evaluation[J]. Complexity, 2018, Article ID 1032643. http://doi.org/10.1155/2018/1032643.
[22] Sheng X Y, Xi M L, Sun J, et al. Quantum-behaved particle swarm optimization with novel adaptive strategies[J].Journal of Algorithm&Computational Technology, 2015, 9(2):143-162.
[23]阮俊虎,王旭坪.中转点变化的应急医疗物资联合运送千扰管理研究[J].运筹与管理,2016, 25(4):114-124.Ruan J H, Wang X P. Disruption management of emergency medical supplies intermodal transportation with updated transit centers[J]. Operations Research and Management Science, 2016, 25(4):114-124.