Abstract:In order to analyze the effect of the correlation between the last-mile delivery and time slot existing in the customer choice procedure of urban distribution service on the operational decisions, such as reception box locating, time slot allocating and vehicle routing, a nested Logit model was used to quantify the customer's choice of delivery service options, and a two-tier nested Logit selection model for urban delivery was proposed. Then a multi-objective optimization model integrated with reception box locating, time slot allocating and vehicle routing was constructed in the purpose of maximizing the delivery amount and minimizing the delivery cost. At last, a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm was constructed to solve this model based on non-dominance sorting, adaptive grid and crowding distance sorting. The analysis shows that, as the attended-home-delivery independence parameter is gradually increased, the substitution of customer demand in different time slots is smaller, the optimal solutions tend to improve the delivery punctuality with increasing the delivery amount, whether it is to minimize the cost or to maximize the number of delivery; on the contrary, with the increase of the reception-box independence parameter, the optimal solutions will decrease the delivery punctuality with reducing the delivery amount.
[1] YANG X, STRAUSSY A K, CURRIEZ C S M, et al. Choice-based demand management and vehicle routing in e-fullment[J]. Transportation Science, 2014, 50(2):473-488. [2] WANG X, ZHAN L, RUAN J, et al. How to choose "last mile" delivery modes for e-fulfillment[J]. Mathematical Problems in Engineering, 2014, 2014:Article ID 417129. [3] 张锦,陈义友.物流"最后一公里"问题研究综述[J].中国流通经济,2015(4):23-32. (ZHANG J, CHEN Y Y. The review of research on the "last-mile" in logistics[J]. China Business and Market, 2015(4):23-32.) [4] 陈淮莉,魏云飞.考虑客户满意度的网络零售配送时隙定价策略[J].计算机工程与应用,2016,52(19):1-6, 106. (CHEN H L, WEI Y F. Pricing strategy of time slot for Internet retailing delivery with considering customer satisfaction[J]. Computer Engineering and Applications, 2016, 52(19):1-6.) [5] 陈义友,张锦,陈以衡,等.基于顾客有限理性的自提点选址研究[J].工业工程与管理,2015,20(6):92-100. (CHEN Y Y, ZHANG J, CHEN Y H, et al. Research on pickup point location based on customers' bounded rationality[J]. Industrial Engineering and Management, 2015, 20(6):92-100.) [6] 陈义友,张锦,曾倩,等.基于顾客选择的自提点选址双层规划模型[J].管理学报,2016,13(12):842-1850. (CHEN Y Y, ZHANG J, ZENG Q, et al. Bi-level optimization model for pickup point location under customer choices[J]. Chinese Journal of Management, 2016, 13(12):1842-1850.) [7] 陈义友,韩珣,曾倩.考虑送货上门影响的自提点多目标选址问题[J].计算机集成制造系统,2016,22(11):2679-2690. (CHEN Y Y, HAN X, ZENG Q. Multi-objective pickup point location problem considering impact of home delivery[J]. Computer Integrated Manufacturing Systems, 2016, 22(11):2679-2690.) [8] PUNAKIVI M, SARANEN J. Identifying the success factors in e-grocery home delivery[J]. International Journal of Retail & Distribution Management, 2001, 29(4):156-163. [9] CAMPBELL A M, SAVELSBERGH M W P. Decision support for consumer direct grocery initiatives[J]. Transportation Science, 2005, 39(3):313-327. [10] AGATZ N, CAMPBELL A, FLEISCHMANN M, et al. Time slot schedule design for e-fulfillment[R]. Rotterdam, Netherlands:Rotterdam School of Management Erasmus University, 2007. [11] AGATZ N, CAMPBELL A, FLEISCHMANN M, et al. Time slot management in attended home delivery[J]. Transportation Science, 2011, 45(3):435-449. [12] EHMKE J F, CAMPBELL A M. Customer acceptance mechanisms for home deliveries in metropolitan areas[J]. European Journal of Operational Research, 2014, 233(1):193-207. [13] CAMPBELL A M, SAVELSBERGH M. Incentive schemes for attended home delivery services[J]. Transportation Science, 2006, 40(3):327-341. [14] 陈淮莉,汪健.能力预留的网络零售配送时隙分配与定价研究[J].中国科技论文,2016,11(7):765-771. (CHEN H L, WANG J. Allocation and pricing of time slot for Internet retailing with capacity reservation[J]. China Sciencepaper, 2016, 11(7):765-771.) [15] 许茂增,余国印.城市配送研究的新进展[J].中国流通经济,2014(11):29-36. (XU M Z, YU G Y. Literature review of internal and external research literature on the urban distribution[J]. China Business and Market, 2014(11):29-36.) [16] NAGY G, SALHI S. Location-routing:Issues, models and methods[J]. European Journal of Operational Research, 2007, 177(2):649-672. [17] 周林,林云,王旭,等.网购城市配送多容量终端选址与多车型路径集成优化[J].计算机集成制造系统,2016,22(4):1139-1147. (ZHOU L, LIN Y, WANG X, et al. Integrated optimization for multiclass terminal location-heterogeneous vehicle routing of urban distribution under online shopping[J]. Computer Integrated Manufacturing Systems, 2016, 22(4):1139-1147.) [18] 李中凯,谭建荣,冯毅雄,等.基于拥挤距离排序的多目标粒子群优化算法及其应用[J].计算机集成制造系统,2008,14(7):1329-1336. (LI Z K, TAN J R, FENG Y X, et al. Multi-objective particle swarm optimization algorithm based on crowding distance sorting and its application[J]. Computer Integrated Manufacturing Systems, 2008, 14(7):1329-1336.) [19] 凌海风,周献中,江勋林,等.改进的约束多目标粒子群算法[J].计算机应用,2012,32(5):1320-1324. (LING H F, ZHOU X Z, JIANG X L, et al. Improved constrained multi-objective particle swarm optimization algorithm[J]. Journal of Computer Applications, 2012, 32(5):1320-1324.) [20] 陈民铀,张聪誉,罗辞勇.自适应进化多目标粒子群优化算法[J].控制与决策,2009,24(12):1851-1855,1864. (CHEN M Y, ZHANG C Y, LUO C Y. Adaptive evolutionary multi-objective particle swarm optimization algorithm[J]. Control and Decision, 2009, 24(12):1851-1855,1864.) [21] 吴斌,倪卫红,樊树海.开放式动态网络车辆路径问题的粒子群算法[J].计算机集成制造系统,2009,15(9):1788-1794. (WU B, NI W H, FAN S H. Particle swarm optimization for open vehicle routing problem in dynamic network[J]. Computer Integrated Manufacturing Systems, 2009, 15(9):1788-1794.)