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

作　　者：宁涛 苟涛[2] 刘向东 Ning Tao;Gou Tao;Liu Xiangdong(Institute of Computer Science and Engineering,Dalian Minzu University,Dalian 116699,China;Institute of Software,Dalian Jiaotong University,Dalian 116028,China)

机构地区：[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

出　　处：《系统仿真学报》2022年第4期797-805,共9页Journal of System Simulation

基　　金：辽宁省经济社会发展基金(20180550499,2022lsljdybkt-014);大连市科技创新金(2021JJ13SN81)。

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。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.

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 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]