多能源混合车队生鲜品配送车辆路径问题研究  

Research on vehicle routing problem of fresh food distribution in multiple energy hybrid fleet

作　　者：周晓晔[1] 戴思聪 ZHOU Xiaoye;DAI Sicong(School of Management,Shenyang University of Technology,Shenyang,Liaoning 110870,China)

机构地区：[1]沈阳工业大学管理学院,辽宁沈阳110870

出　　处：《沈阳工业大学学报（社会科学版）》2024年第3期301-310,共10页Journal of Shenyang University of Technology(Social Sciences)

基　　金：辽宁省社会科学规划基金重大项目(L22ZD010)。

摘　　要：针对同时考虑取送货和分时电价的电动车与燃油车混合车队车辆路径问题,以车辆固定成本、行驶成本、制冷成本、货损成本、时间窗成本、碳排放成本和充电成本之和最小为目标,构建生鲜品配送车辆路径优化模型,设计融合邻域搜索的遗传模拟退火混合算法并求解。结果表明:相比于取送分离,同时取送货模式能够显著提升配送效率,提高车辆装载率;通过技术升级适当增加电动车的电池容量,能够弱化车辆路径方案对充电设施的依赖程度,有效降低配送成本;通过与遗传算法、遗传变邻域混合算法运行结果对比,验证本文算法的有效性,为冷链物流企业在配送环节实现节能减排、降本增效提供借鉴和参考。Aiming at the vehicle routing problem of the mixed fleet of electric vehicles and fuel vehicles considering both pick-up and delivery and time of use electricity tariffs,a vehicle routing optimization model for fresh food distribution has been constructed with the objective of minimizing the sum of the fixed vehicle cost,driving cost,refrigeration cost,cargo damage cost,time window cost,carbon emission cost and charging cost,and a hybrid genetic simulated annealing algorithm integrating neighborhood search is designed for solution.The results show that compared with the separation of pickup and delivery,the simultaneous pickup and delivery mode can significantly improve the distribution efficiency and vehicle loading rate;properly increasing the battery capacity of electric vehicles through technical upgrading can weaken the dependence of vehicle routing schemes on charging facilities and effectively reduce distribution costs;by comparing with the running results of the genetic algorithm and hybrid genetic algorism-variable neighborhood search algorithm,the effectiveness of the algorithm is verified.References are provided for cold chain logistics enterprises to achieve energy conservation and emission reduction,cost reduction and efficiency increase in the distribution link.

关 键 词：混合车队 遗传模拟退火混合算法 冷链物流 电动车配送 取送货 分时电价 

分 类 号：F259.2[经济管理—国民经济]