Planning model of feeder shipping network for container liners under considering shipper perference
-
摘要: 为了增加内支线集装箱班轮航线网络的货运需求量, 以最大船型限制、航线运营补贴与干支线配合为约束条件, 以航线网络结构、适配船型与班期密度为决策变量, 构建了考虑货主偏好的集装箱内支线班轮航线网络规划模型; 为了评估规划航线对不同偏好货主的吸引力, 在获得航线的集装箱运输时间与价格后, 基于Logit模型计算了规划航线与市场现有航线的货主选择比例; 设计了求解模型的智能启发式算法, 在规划方案评价过程中计算了航次时间、航线成本、单箱运价与货运需求, 在方案改善过程中调整了航线的挂靠港口与挂靠顺序; 设定大连港为干线港口, 渤海湾内12个港口为支线港口, 规划了内支线集装箱班轮航线网络。计算结果表明: 12个支线港共开设了7条航线, 市场货运总需求为5 208TEU, 规划航线的货运需求量为4 420TEU; 规划航线的货主选择比例达到85%;无论货主偏好运输时间或成本, 规划航线在各支线港的货主选择比例皆超过60%。可见, 考虑货主偏好的内支线班轮航线网络规划模型是有效的; 开设直达航线有助于吸引时间偏好货主; 开设串挂航线与提高运营补贴有助于吸引成本偏好货主; 采用货主选择过程代替到港时间窗约束会提升模型优化效果。Abstract: To increase the freight demand of feeder shipping network for container liners, a planning model of the network under considering shipper preference was proposed. In the model, the constraints were permitted capacity limit, route operation subsidy and hub-and-spoke cooperation, and the decision variables were route network structure, ship capacity and service frequency. To evaluate the attraction of planning network to shippers with different preferences, the selection proportions of shippers between planning network and existing network were calculated by Logit model after the shipping time and freight of containers were gotten. To solve the model effectively, an intelligent heuristic algorithm was designed, the voyage time, voyage cost, freight per container and freight demand were calculated in the evaluation process ofplanning scheme, and the affiliated ports and sequence of routes were adjusted in the improvement process of planning scheme. The Dalian Port was taken as main port, the 12 ports in Bohai Gulf were taken as feeder ports, and the feeder shipping network for container liners was planned. Calculation result shows that 7 routes are planned among 12 feeder ports. There are 5 208 TEU containers in market, and the freight demand of planned shipping network is 4 420 TEU. The selection proportion of shippers for planning shipping network reaches 85%. When shipper preference is shipping time or cost, the selection proportion of planning shipping network at every feeder port exceeds 60%. Therefore, the planning model of feeder shipping network for container lines under considering shipper preference is effective. The direct routes contribute to attract the shippers with time preference. The multi-anchored routes and higher operation subsidy contribute to attract the shippers with cost preference. Replacing time-window constraint with shipper selection process can improve the optimization effect of the model.
-
表 5 不同时间偏好系数下的计算结果
Table 5. Calculation results under different time preference coefficients
下载: 导出CSV
表 6 不同成本偏好系数下的计算结果
Table 6. Calculation results under different cost preference coefficients
下载: 导出CSV
-
[1] KARLAFTIS M G, KEPAPTSOGLOU K, SAMBRACOS E. Containership routing with time deadlines and simultaneous deliveries and pick-ups[J]. Transportation Research Part E: Logistics and Transportation Review, 2009, 45 (1): 210-221. doi: 10.1016/j.tre.2008.05.001 [2] TRAN N K, HAASIS H D. Literature survey of network optimization in container liner shipping[J]. Flexible Services and Manufacturing Journal, 2015, 27 (2/3): 139-179. [3] SONG Dong-ping, DONG Jing-xin. Long-haul liner service route design with ship deployment and empty container repositioning[J]. Transportation Research Part B: Methodological, 2013, 55 (9): 188-211. [4] LO H K, AN Kun, LIN Wei-hua. Ferry service network design under demand uncertainty[J]. Transportation Research Part E: Logistics and Transportation Review, 2013, 59: 48-70. doi: 10.1016/j.tre.2013.08.004 [5] WANG Shuai-an, MENG Qiang. Liner shipping network design with deadlines[J]. Computers and Operations Research, 2014, 41 (1): 140-149. [6] ZHENG Jian-feng, MENG Qiang, SUN Zhuo. Impact analysis of maritime cabotage legislations on liner hub-and-spoke shipping network design[J]. European Journal of Operational Research, 2014, 234 (3): 874-884. doi: 10.1016/j.ejor.2013.10.045 [7] JI Ming-jun, SHEN Li-xin, SHI Bai-shun, et al. Routing optimization for multi-type containerships in a hub-and-spoke network[J]. Journal of Traffic and Transportation Engineering: English Edition, 2015, 2 (5): 362-372. doi: 10.1016/j.jtte.2015.08.008 [8] KEPAPTSOGLOU K, FOUNTAS G, KARLAFTIS M G. Weather impact on containership routing in closed seas: A chance-constraint optimization approach[J]. Transportation Research Part C: Emerging Technologies, 2015, 55: 139-155. doi: 10.1016/j.trc.2015.01.027 [9] KARSTEN C V, PISINGER D, ROPKE S, et al. The time constrained multi-commodity network flow problem and its application to liner shipping network design[J]. Transportation Research Part E: Logistics and Transportation Review, 2015, 76: 122-138. doi: 10.1016/j.tre.2015.01.005 [10] LEE C Y, LEE H L, ZHANG Ji-heng. The impact of slow ocean steaming on delivery reliability and fuel consumption[J]. Transportation Research Part E: Logistics and Transportation Review, 2015, 76: 176-190. doi: 10.1016/j.tre.2015.02.004 [11] 殷明, 时恒, 金甲焕. 集装箱班轮公司航次运力销售过程优化模型[J]. 交通运输工程学报, 2015, 15 (2): 79-89. doi: 10.3969/j.issn.1671-1637.2015.02.011YIN Ming, SHI Heng, KIM K H. Sales process optimization model of voyage capacity for container line[J]. Journal of Traffic and Transportation Engineering, 2015, 15 (2): 79-89. (in Chinese). doi: 10.3969/j.issn.1671-1637.2015.02.011 [12] GELAREH S, NICKEL S, PISINGER D. Liner shipping hub network design in a competitive environment[J]. Transportation Research Part E: Logistics and Transportation Review, 2010, 46 (6): 991-1004. doi: 10.1016/j.tre.2010.05.005 [13] KASHIHA M, THILL J C, DEPKEN C A. Shipping route choice across geographies: coastal vs. landlocked countries[J]. Transportation Research Part E: Logistics and Transportation Review, 2016, 91: 1-14. doi: 10.1016/j.tre.2016.03.012 [14] EISELT H A, MARIANOV V. A conditional p-hub location problem with attraction functions[J]. Computers and Operations Research, 2009, 36 (12): 3128-3135. doi: 10.1016/j.cor.2008.11.014 [15] CHEN Rong-ying, DONG Jing-xin, LEE C Y. Pricing and competition in a shipping market with waste shipments and empty container repositioning[J]. Transportation Research Part B: Methodological, 2016, 85: 32-55. doi: 10.1016/j.trb.2015.12.0121016/j.tre.2013.05.006 [16] AN K, LO H K. Ferry service network design with stochastic demand under user equilibrium flows[J]. Transportation Research Part B: Methodological, 2014, 66: 70-89. doi: 10.1016/j.trb.2013.10.008 [17] CHEN Kang, YANG Zhong-zhen, NOTTEBOOM T. The design of coastal shipping services subject to carbon emission reduction targets and state subsidy levels[J]. Transportation Research Part E: Logistics and Transportation Review, 2014, 61 (1): 192-211. [18] LEE H, LEE K D, CHOO S. The effects of the emission cost on route choices of international container ships[J]. Mathematical Problems in Engineering, 2016, 2016: 1-13. [19] WANG Shuai-an, MENG Qiang. Reversing port rotation directions in a container liner shipping network[J]. Transportation Research Part B: Methodological, 2013, 50 (5): 61-73. [20] WANG Hua, MENG Qiang, ZHANG Xiao-ning. Gametheoretical models for competition analysis in a new emerging liner container shipping market[J]. Transportation Research Part B: Methodological, 2014, 70: 201-227. doi: 10.1016/j.trb.2014.09.006 [21] WANG Hua, WANG Shuai-an, MENG Qiang. Simultaneous optimization of schedule coordination and cargo allocation for liner container shipping networks[J]. Transportation Research Part E: Logistics and Transportation Review, 2014, 70 (1): 261-273. [22] WANG Shuai-an, WANG Hua, MENG Qiang. Itinerary provision and pricing in container liner shipping revenue management[J]. Transportation Research Part E: Logistics and Transportation Review, 2015, 77: 135-146. doi: 10.1016/j.tre.2014.06.020 [23] AGARWAL R, ERGUN O. Ship scheduling and network design for cargo routing in liner shipping[J]. Transportation Science, 2008, 42 (2): 175-196. doi: 10.1287/trsc.1070.0205 [24] BROUER B D, DIRKSEN J, PISINGER D, et al. The vessel schedule recovery problem (VSRP) -a MIP model for handling disruptions in liner shipping[J]. European Journal of Operational Research, 2013, 224 (2): 362-374. doi: 10.1016/j.ejor.2012.08.016 [25] BROUER B D, ALVAREZ J F, PLUM C E M, et al. A base integer programming model and benchmark suite for linear-shipping network design[J]. Transportation Science, 2014, 48 (2): 281-312. doi: 10.1287/trsc.2013.0471 -
点击查看大图
图(5) / 表(9)
计量
- 文章访问数: 609
- HTML全文浏览量: 117
- PDF下载量: 635
- 被引次数: 0
