多油品供给受限下多油库被动配送车辆路径问题研究

doi:10.16381/j.cnki.issn1003-207x.2018.1472

Abstract

Abstract: The insufficient supply of refined oil will cause that the oil gas stationcan't fully meet the orders. How to arrange the reasonable distribution of limited oil is essential to ensure the safety of energy supply. To this end, the distribution priority of different customers under limited supply is considered, distribution planning, vehicle scheduling, path optimization and other oil distribution network planning activities are carried out, in-depth study on the Multiple Depot Vehicle Routing Problem (MDVRP) with multi-oil supply constraints is conducted. Firstly, a multi-objective optimization model of vehicle routing for multi-oil products and multi-oil depots is constructed, which considers the priority of demand and the cost of distribution. Secondly, the Multi-Objective Particle Swarm Optimization (MOPSO) is used to solve the model to achieve efficient vehicle scheduling and oil distribution routing optimization. Finally, based on the data information of CNPC in some oil depots and fueling stations in Qingdao, an oil distribution network is constructed for empirical testing. The results of the example show that the Pareto optimal set is generated after the optimization of vehicle routing, the distribution cost is significantly reduced, and the delivery satisfaction rate is significantly improved, which further verifies the feasibility and effectiveness of the model and related algorithms.The model and algorithm can be further extended to various supply and demand situations, which is helpful to solve the distribution problem of refined oil products with different priority of gas stations.

Key words: MDVRP, resource constrained, refined oil distribution, multi-objective optimization, MOPSO

CLC Number:

F252.5

XU Xiao-feng, LIN Zi-ru, ZHOU Peng. Research on Vehicle Routing Problem of Multiple Oil Depot Passive Distribution under Multi Oil Supply Constraints[J]. Chinese Journal of Management Science, 2021, 29(5): 157-165.

References

[1] 王博弘,梁永图,张浩然,等.成品油二次配送研究进展[J].油气储运,2018,37(2):121-126.
[2] 李敏, 倪少权, 周凌,等. 基于订单邻域的成品油二次配送中带时间窗车辆路径规划问题[J]. 计算机集成制造系统, 2015, 21(8):2158-2169.
[3] 王旭坪, 詹红鑫, 孙自来,等. 基于蚁群禁忌混合算法的成品油多舱配送路径优化研究[J]. 系统工程理论与实践, 2017, 37(12):3215-3226.
[4] Xu Xiaofeng, Hao Jun, Deng Yirui, et al. Design optimization of resource combination for collaborative logistics network under uncertainty[J]. Applied Soft Computing, 2017, 560(7):684-691.
[5] Olivera A, Viera O. Adaptive memory programming for the vehicle routing problem with multiple trips[J]. Computers & Operations Research, 2005, 34(1):28-47.
[6] Brown G G, Graves G W. Real-time dispatch of petroleum tank trucks[J]. Management Science, 1979, 27(1):19-32.
[7] 余晓钟, 刘鸿渊, 陈健声. 基于缺货条件的成品油二次运输成本优化[J]. 西南石油大学学报(自然科学版), 2009, 31(5):167-170, 209.
[8] 王剑, 王红卫. 基于混合遗传算法的资源受限的运输任务调度[J]. 计算机工程与应用, 2007, 43(31):34-38.
[9] Wang Xuping, Zhan Hongxin, Zhang Jun. Research of oil product secondary distribution optimization based on collaborative distribution[J]. Procedia Computer Science, 2015, 60(1):1367-1376.
[10] 唐亮, 何杰, 靖可,等. 时间窗口约束下基于改进蚁群算法的协同制造调度研究[J]. 中国管理科学, 2018, 26(4):97-107.
[11] 陈玉光,陈志祥.基于准时送货和最小耗油的配送车辆路径问题研究[J].中国管理科学,2015,23(S1):156-164.
[12] 石琴, 陈朝阳, 覃运梅. 多目标物流网络优化模型的研究[J]. 中国管理科学, 2005,(4):40-43.
[13] 裴军, 刘心报, 范雯娟,等. 基于生产与运输集成的供应链调度优化问题[J]. 中国管理科学, 2012, 20(S2):586-593.
[14] Xu Xiaofeng, Hao Jun,Yu Lean, et al. Fuzzy optimal allocation model for task-resource assignment problem in collaborative logistics network[J]. IEEE Transactions on Fuzzy Systems, 2019,75(5):1112-1125.
[15] 葛显龙, 许茂增, 王伟鑫. 多车型车辆路径问题的量子遗传算法研究[J]. 中国管理科学, 2013, 21(1):125-133.
[16] 潘雯雯, 郭海湘, 周光勇,等. 基于两阶段算法的需求可拆分多车型车辆路径问题[J]. 中国管理科学, 2016, 24(S1):55-61.
[17] 郎茂祥, 胡思继. 用混合遗传算法求解物流配送路径优化问题的研究[J]. 中国管理科学, 2002, 10(5):51-56.
[18] Allahviranloo M, Chow J, Recker W W.Selective vehicle routing problems under uncertainty without recourse[J]. Transportation Research Part E, 2014, 62(2):68-88.
[19] 王华东, 李巍. 粒子群算法的物流配送路径优化研究[J]. 计算机仿真, 2012, 29(5):243-246.
[20] 关菲, 张强. 模糊多目标物流配送中心选址模型及其求解算法[J]. 中国管理科学, 2013, 21(S1):57-62.
[21] Luo Jianping, Chen Minrong. Multi-phase modified shuffled frog leaping algorithm with extremal optimization for the MDVRP and the MDVRPTW[J]. Computers & Industrial Engineering, 2014, 72(1):84-97.
[22] 毕志升, 郑炯彬, 蔡桂艳. 基于高维多目标优化的多车场车辆路径问题[J]. 计算机与数字工程, 2017, 45(7):1298-1304, 1317.
[23] 李霄玉, 姚骏. 解决多目标旅行商问题的改进NSGA-Ⅱ算法[J]. 工业控制计算机, 2018, 31(4):103-104.
[24] 郭海湘, 杨娟, 於世为,等. 带服务优先级的煤矿物资配送车辆路径问题[J]. 系统管理学报, 2012, 21(1):133-144.
[25] Ghoddousi P, Eshtehardian E, Jooybanpour S, et al. Multi-mode resource-constrained discrete time-cost-resource optimization in project scheduling using non-dominated sorting genetic algorithm[J]. Automation in Construction, 2013, 30(30):216-227.
[26] Chakrabortty R K, Sarker R A, Essam D L. Multi-mode resource constrained project scheduling under resource disruptions[J]. Computers and Chemical Engineering, 2016, 88(5):13-29.
[27] Xu Xiaofeng, Zhang Wei, Li Ning, et al. A bi-level programming model of resource matching for collaborative logistics network in supply uncertainty environment[J]. Journal of the Franklin Institute, 2015, 352(9):3873-3884.
[28] Geiger M J. A multi-threaded local search algorithm and computer implementation for the multi-mode, resource-constrained multi-project scheduling problem[J]. European Journal of Operational Research, 2017, 256(3):729-741.
[29] El-Abbasy M S, Elazouni A, Zayed T. MOSCOPEA:Multi-objective construction scheduling optimization using elitist non-dominated sorting genetic algorithm[J]. Automation in Construction,2016,71:153-170.
[30] Maghsoudlou H, Afshar-Nadjafi B, Niaki S T A. A multi-objective invasive weeds optimization algorithm for solving multi-skill multi-mode resource constrained project scheduling problem[J]. Computers and Chemical Engineering, 2016, 88:157-169.
[31] Deb K, Agrawal S, Pratap A, et al. A fast elitist non-dominated sorting genetic algorithms for multi-objective optimization:NSGA-II[J]Lecture Notes in Computer Science, 2000, 1917:849-858.
[32] 王金华, 尹泽勇. 基于NSGA-Ⅱ和MOPSO融合的一种多目标优化算法[J]. 计算机应用, 2007, 27(11):2817-2820, 2823.

Research on Vehicle Routing Problem of Multiple Oil Depot Passive Distribution under Multi Oil Supply Constraints

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 9

Metrics

Comments

Recommended 10

[1]	PENG Wu-liang, MA Xiao-jing. A Bi-objective Optimization Method for Tactical Project Planning [J]. Chinese Journal of Management Science, 2021, 29(2): 69-77.
[2]	DONG Xue-fan, LIU Yi-jun, LIAN Ying. Entropy-Controlled Principle based Multi-objective Industrial Structure Optimization Model in the Tertiary Industry:A Case Study of Beijing [J]. Chinese Journal of Management Science, 2017, 25(9): 53-62.
[3]	DING Qiu-lei. Model of Disruption Management for the Change of Time Window Based on Human Behavior in Logistic Distribution [J]. Chinese Journal of Management Science, 2015, 23(5): 89-97.
[4]	GE Huai-zhi, ZHANG Jin-long. A Method for Public Housing Matching Assignment Based on Axiomatic Design and Excess Functionality [J]. Chinese Journal of Management Science, 2015, 23(1): 111-120.
[5]	LI Shuang-lin, MA Zu-jun, ZHENG Bin, DAI Ying. Fuzzy Multi-Objective Location-Multimodal Transportation Problem for Relief Delivery during the Initial Post-earthquake Period [J]. Chinese Journal of Management Science, 2013, (2): 144-151.
[6]	WANG Ke-xi, YUAN Ji-jun, HUANG Min-mei, CHEN Wei-min. Multi-Objective Intelligent Optimization Design Method for Multi-Platform Based Scaled-Based Product Family [J]. Chinese Journal of Management Science, 2011, 19(4): 111-119.
[7]	QI Er-shi, LI Hui, LIU liang. Research on Collaborative Resource Optimization of Virtual Enterprises Based on Genetic Algorithm [J]. Chinese Journal of Management Science, 2011, 19(1): 77-83.
[8]	LI Qiang, ZHANG Jing. Research On Multi-Resource Constrained Project Integration Management Optimization Problem [J]. Chinese Journal of Management Science, 2008, 20(6): 123-129.
[9]	WAN Wei, CAI Chen, WANG Chang-feng. Critical Chain PM in Single-Resource Constrained Environment [J]. Chinese Journal of Management Science, 2003, (2): 70-75.