考虑低碳约束的生鲜农产品冷链物流策略仿真研究

doi:10.16182/j.issn1004731x.joss.20-0903

系统仿真学报 ›› 2022, Vol. 34 ›› Issue (4): 797-805.doi: 10.16182/j.issn1004731x.joss.20-0903

考虑低碳约束的生鲜农产品冷链物流策略仿真研究

宁涛^1,²(), 苟涛², 刘向东¹()

^1.大连民族大学计算机科学与工程学院，辽宁大连 116699
^2.大连交通大学软件学院，辽宁大连 116028

收稿日期:2020-11-26 修回日期:2021-01-05 出版日期:2022-04-30 发布日期:2022-04-20
通讯作者: 刘向东 E-mail:daliannt@126.com
作者简介:宁涛(1979-)，男，博士，教授，硕士生导师，研究方向为物流管理，交通规划。E-mail：daliannt@126.com
基金资助:
辽宁省经济社会发展基金(20180550499);大连市科技创新金(2021JJ13SN81)

Simulation on Cold Chain Distribution Path of Fresh Agricultural Products Under Low-carbon Constraints

Tao Ning^1,²(), Tao Gou², Xiangdong Liu¹()

^1.Institute of Computer Science and Engineering, Dalian Minzu University, Dalian 116699, China
^2.Institute of Software, Dalian Jiaotong University, Dalian 116028, China

Received:2020-11-26 Revised:2021-01-05 Online:2022-04-30 Published:2022-04-20
Contact: Xiangdong Liu E-mail:daliannt@126.com

摘要/Abstract

摘要：

生鲜农产品的新鲜度配送要求可能增加其冷链配送过程的碳排放量。在对碳税机制定量分析的基础上，建立以最小化碳排放量和最小化配送综合成本为目标的数学模型；综合分析物流配送中的产品配送量、配送时间以及装卸货时间等常规因素，提出了一种改进的基于自适应旋转角的量子蚁群算法；将所提出的方法通过实验仿真应用于生鲜配送仿真算例，并将结果与已经存在的算法进行比较，结果表明：该方法可以有效优化生鲜农产品冷链物流配送路径，同时降低碳排放及配送成本。

关键词: 车辆路径问题, 碳税机制, 量子蚁群算法, 冷链物流仿真

Abstract:

The freshness distribution requirements of fresh agricultural products may increase the carbon emissions of the cold chain distribution process. A cold chain distribution scheduling strategy and simulation method for the fresh agricultural products under low-carbon constraints is proposed. Based on the quantitative analysis of the carbon tax mechanism, a mathematical model of minimizing the carbon emissions and minimizing the overall cost of distribution is established. Comprehensively analyzing the conventional factors such as the product delivery volume, delivery time and loading and unloading time in logistics distribution, an improved quantum ant colony algorithm based on adaptive rotation angle is proposed. The proposed method is applied to a simulation example of fresh food distribution. The experimental results are compared with the results of the existing algorithms, and verify that the proposed method can effectively optimize the cold chain logistics distribution path of fresh agricultural products and reduce the carbon emissions and distribution costs.

Key words: vehicle routing problem, carbon tax, hybrid ant colony algorithm, simulation of cold chain logistics

中图分类号:

TP301

宁涛, 苟涛, 刘向东. 考虑低碳约束的生鲜农产品冷链物流策略仿真研究[J]. 系统仿真学报, 2022, 34(4): 797-805.

Tao Ning, Tao Gou, Xiangdong Liu. Simulation on Cold Chain Distribution Path of Fresh Agricultural Products Under Low-carbon Constraints[J]. Journal of System Simulation, 2022, 34(4): 797-805.

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参考文献 27

1	帅传敏, 张钰坤. 中国消费者低碳产品支付意愿的差异分析-基于碳标签的情景实验数据[J]. 中国软科学, 2013(7): 61-70.
	Chuanmin Shuai, Zhang Yukun. Difference Analysis of Chinese Consumers Willingness to Pay for Low-Carbon Products-Scenario Experimental Data Based on Carbon Labels[J]. China Soft Science, 2013(7): 61-70.
2	Piecyk M I, Mckinnon A C. Forecasting the Carbon Foot-Print of Road Freight Transport in 2020[J]. International Journal of Production Economics(S0925-5273), 2010, 128(1): 31-42.
3	Dantzing G B, Ramser J H. The Truck Dispatching Problem[J]. Management Science(S0025-1909), 1959, 6(1): 80-91.
4	Solnmon M M, Desrosiers J. Time Window Constraint Routing and Scheduling Problems[J]. Transportation Science(S0041-1655), 1988, 22(1): 1-13.
5	Jabali O, Leus R, Van Woensel T, et al. Self-Imposed Time Windows in Vehicle Routing Problems[J]. OR Spectrum(S0171-6468), 2015, 37(2): 331-352.
6	涂海宁, 徐星. 改进蚁群算法下的物料配送路径优化研究[J]. 机械设计与制造, 2017(8): 265-268.
	Tu Haining, Xu Xing. Research on Material Distribution Path Optimization Based on Improved ant Colony Algorithm[J]. Machinery Design and Manufacturing, 2017(8): 265-268.
7	夏扬坤, 符卓. 带软时间窗的连锁超市配送车辆路径问题[J]. 信息与控制, 2018, 47(5): 599-605.
	Xia Yangkun, Fu Zhuo. Distribution Vehicle Routing Problem in Supermarket Chains with Soft Time Windows[J]. Information and Control, 2018, 47(5): 599-605.
8	Franceschette A, Honhon D, Woensel T V, et al. The Time-Depend Pollution-Routing Problem[J]. Transportation Research Part B(Methodological)(S0191-2615), 2013, 56(C): 265-293.
9	Xiao Y, Konak A. The Heterogeneous Green Vehicle Routing and Scheduling Problem with Time-Varying Traffic Congestion[J]. Transportation Research Part E (Logistics and Transportation Review)(S1366-5545), 2016, 100(88): 146-166.
10	Wen L, Catay B, Eglese R. Finding a Minimum Cost Path Between a Pair of Nodes in a Time-Varying Road Network with a Congestion Charge[J]. European Journal of Operational Research(S0377-2217), 2014, 236(3): 915-923.
11	Fan Houming, Liu Pengcheng, Wu Jiaxin, et al. VRP and Hybrid Variable Neighborhood Search Algorithm for Random Simultaneous Collection of Goods with Demand for Goods Collection[J]. System Engineering Theory and Practice(S1000-6788), 2019, 39(10): 2646-2659.
12	Fan Houming, Wu Jiaxin, Geng Jing, et al. Vehicle Routing Problem with Fuzzy Demand and Time Widow and Hybrid Genetic Algorithm Solution[J]. Journal of Systems Managements(S1816-6075), 2020, 29(1): 107-118.
13	康凯, 韩杰, 普玮, 等. 生鲜农产品冷链物流低碳配送路径优化研究[J]. 计算机工程与应用, 2019, 55(2):259-265.
	Kang Kai, Han Jie, Pu Wei, et al. Optimization of Low-Carbon Distribution Path for Cold Chain Logistics of Fresh Agricultural Products[J]. Computer Engineering and Applications, 2019, 55(2): 259-265.
14	Li Shunyong, Dan Bin, Ge Xianlong. Low Carbon Vehicle Routing Optimization Model and Algorithm in Multi-Channel Time-Varying Network[J]. Computer Integrated Manufacturing Systems(S1006-5911), 2019, 25(2): 454-468.
15	Ning Tao, Wang Xuping, Hu Xiangpei. Interference Management Decision Model for Delivery Vehicle Scheduling under Driving Delay[J]. System Engineering Theory and Practice(S1000-6788), 2019, 39(5): 1236-1245.
16	Ning Tao, Wang Xuping, Hu Xiangpei. Research on the Management Method of Terminal Logistics Interference Based on Prospect Theory[J]. System Engineering Theory and Practices(S1000-6788), 2019, 39(3): 673-681.
17	Ning T, Wang X P. Study on Disruption Management Strategy of Job-Shop Scheduling Problem Based on Prospect Theory[J]. Journal of Cleaner Productions(S0959-6526), 2018(194): 174-178.
18	Ning Tao, Gou Tao, Zhang Peng. Disruption Management Strategy of Terminal Logistics under Accidental Travel Time Delay Based on Prospect Theory[J]. Journal of Intelligent & Fuzzy Systems(S1875-8967), 2019, 37(6): 8371-8379.
19	方文婷, 艾时钟, 王晴, 等. 基于混合蚁群算法的冷链物流配送路径优化研究[J]. 中国管理科学, 2019, 27(11): 107-115.
	Fang Wenting, Ai Shizhong, Wang Qing, et al. Research on Cold Chain Logistics Distribution Path Optimization Based on Hybrid ant Colony Algorithm[J]. China Management Science, 2019, 27(11): 107-115.
20	赵志学, 李夏苗, 周鲜成, 等. 考虑交通拥堵的冷链物流城市配送的GVRP研究[J]. 计算机工程与应用, 2020, 56(1): 224-231.
	Zhao Zhixue, Li Xiamiao, Zhou Xiancheng, et al. GVRP Research on Cold Logistics City Distribution Considering Traffic Congestion[J]. Computer and Applications, 2020, 56(1): 224-231.
21	Rao Weizhen, Duan Zhongfei, Wang Bingcheng, et al. Research on the Theoretical Boundary of Distance and Energy Saving of Cooperative Vehicle Routing Problem[J]. Journal of System Managements(S1005-2542), 2019, 28(4): 697-707.
22	Ma Qizhuo, Wang Jian, Song Haiqing. Small-Area Low-Carbon Multi-Vehicle Low-Carbon VRP in Urban Areas: A Case Study of Zhuhai Express Co, Ltd.'s Regional Receiving Network[J]. Journal of Managements, Engineerings(S1943-5479), 2016, 30(4): 153-159.
23	Rao Weizhen, Jin Chun, Wang Xinhua, et al. Low Carbon VRP Problem Model and Solution Strategy Considering Road Slope Factor[J]. System Engineering Theory and Practices(S1000-6788), 2014, 34(8): 2092-2105.
24	陈志, 江治杰, 刘瑶. 基于改进蚁群算法的不同路段低碳物流路径优化研究[J]. 生态经济, 2019, 35(12): 53-59, 66.
	Chen Zhi, Jiang Zhijie, Liu Yao. Optimization of Low Carbon Logistics Paths in Different Links Based on Improved Ant Colony Algorithm[J]. Ecp-economics, 2019, 35(12): 53-59, 66.
25	Xiao Yiyong, Zhao Qiuhong, Kaku I, et al. Development of a Fuel Consumption Optimization Model for the Capacitated Vehicle Routing Problem[J]. Computer & Operations Researchs(S0305-0548), 2012, 39(7): 1419-1431.
26	李琳, 范休军. 零货商主导下生鲜农产品供应链的定价策略对比研究[J]. 中国管理科学, 2015, 23(12): 113-123.
	Li Lin, Fan Xiujun. Comparative Study on Pricing Strategies of Fresh Agricultural Product Supply Chains Dominated by Retailers[J]. China Management Science, 2015, 23(12): 113-123.
27	Li B B, Wang L. A Hybrid Quantum-Inspired Genetic Algorithm for Multi-Objective Flow Shop Scheduling[J]. IEEE Transactions on Systems, Man and Cyberneticss(S0742-597X), 2007, 37(3): 576-591.

编号	客户点坐标/km	客户需求量/t	需求时段	卸货时间/min
0	(0,0)
1	(60,140)	1.5	(06:30-09:30)	20
2	(30,114)	2.5	(05:30-09:30)	10
3	(40,36)	3.0	(06:30-10:00)	25
4	(48,96)	6.0	(06:30-09:30)	20
5	(52,120)	3.0	(06:30-10:00)	25
6	(92,154)	2.5	(07:00-09:30)	25
7	(92,66)	5.0	(05:30-10:00)	20
8	(94,100)	5.0	(06:00-09:30)	15
9	(108,188)	6.0	(06:30-09:30)	15
10	(44,160)	6.0	(06:30-10:00)	15
11	(20,54)	4.0	(07:00-10:00)	20
12	(108,32)	5.0	(06:00-10:30)	15
13	(130,88)	5.0	(05:30-10:00)	15

优化目标	配送距离/km	综合成本(元)	碳税成本(元)
成本最低	1 989	4 393	3 978
路径最短	1 879	4 459	4 163

优化目标	(α,β)
优化目标	(1,1)	(1,2)	(1,3)	(2,1)	(2,2)
配送车辆数	4	5	5	4	5
最优结果Z	4 435	4 404	4 393	4 418	4 407
碳税成本(元)	4 407	4 105	3 978	4 272	4 113

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考虑低碳约束的生鲜农产品冷链物流策略仿真研究

Simulation on Cold Chain Distribution Path of Fresh Agricultural Products Under Low-carbon Constraints

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