文章摘要
王勇,王静媛,苟梦圆,罗思妤.基于时间窗和多仓温控的生鲜商品配送车辆路径优化问题[J].包装工程,2024,45(5):263-275.
WANG Yong,WANG Jingyuan,GOU Mengyuan,LUO Siyu.Fresh Commodity Distribution Vehicle Routing Optimization Based on Time Windows and Multi-compartment Temperature Control[J].Packaging Engineering,2024,45(5):263-275.
基于时间窗和多仓温控的生鲜商品配送车辆路径优化问题
Fresh Commodity Distribution Vehicle Routing Optimization Based on Time Windows and Multi-compartment Temperature Control
投稿时间:2023-09-28  
DOI:10.19554/j.cnki.1001-3563.2024.05.032
中文关键词: 生鲜商品配送  多仓温控  时间窗  CW-NSGA-Ⅱ
英文关键词: fresh commodity distribution  multi-compartment temperature control  time window  CW-NSGA-Ⅱ
基金项目:国家自然科学基金(72371044,71871035);重庆市教委科学技术研究重大项目(KJZD-M202300704);重庆市自然科学基金面上项目(CSTB2022NSCQ-MSX0535);巴渝学者青年项目(YS2021058)
作者单位
王勇 重庆交通大学重庆 400074 
王静媛 重庆交通大学重庆 400074 
苟梦圆 重庆交通大学重庆 400074 
罗思妤 重庆交通大学重庆 400074 
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中文摘要:
      目的 针对当前生鲜商品配送效率低和成本高等问题,采用车仓温度可控的多仓车辆作为配送装备,并结合时间窗等约束,研究基于时间窗和多仓温控的生鲜商品配送车辆路径优化问题。方法 建立最小化物流运营成本和车辆使用数量的双目标模型,然后设计基于Clarke-Wright节约算法的非支配排序遗传算法(CW-NSGA-Ⅱ)求解该模型。利用CW节约算法生成初始配送路径,以提高初始解的质量,并设计精英迭代策略,以提高算法的寻优性能。结果 基于改进的Solomon算例,将文中所提算法与多目标粒子群算法、多目标蚁群算法、多目标遗传算法进行了对比,验证了CW-NSGA-Ⅱ算法的求解性能。结合实例,对多仓车辆使用数量、温控成本和运营成本等指标进行对比分析,结果表明,经优化后多仓车辆使用数量减少了35.7%,温控成本减少了39.2%,物流运营总成本减少了47.7%。结论 文中所提模型和算法能够有效优化配送路径,降低运营成本,为构建高效率、低成本的生鲜配送网络提供了理论支持和决策参考。
英文摘要:
      Aiming at the inefficient and high-cost fresh commodity distribution, the work aims to study the fresh commodity distribution route optimization based on time windows and multi-compartment temperature control by adopting multi-compartment vehicles with temperature controlled compartments as distribution equipment and applying time windows and other constraints. Firstly, the bi-objective model was established to minimize logistics operating cost and the number of vehicles. Then, the non-dominated sorting genetic algorithm based on the Clarke-Wright saving algorithm (CW-NSGA-Ⅱ) was designed to solve the model. Among them, the initial population was generated by the Clarke-Wright saving algorithm, which improved the quality of the initial solution, and an elite iterative strategy was designed to improve the optimization performance.Based on the improved Solomon example, the proposed algorithm was compared with the multi-objective particle swarm algorithm, multi-target ant colony algorithm and multi-target genetic algorithm, verifying the solution performance of the CW-NSGA-Ⅱ. Combined with a case study, the indicators such as the number of multi-compartment vehicles, temperature control costs and operating costs were compared and analyzed. The results showed that the number of optimized multi-compartment vehicles was reduced by 35.7%, the temperature control cost was reduced by 39.2%, and the total operating cost was reduced by 47.7%. The proposed model and algorithm can effectively optimize the distribution route, reduce the total operating cost, and provide theoretical support and decision-making reference for the construction of the efficient and low-cost fresh distribution network.
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