随机需求下考虑碳排放的多温共配路径优化模型及算法  

Model and Algorithm for Multi-temperature Joint Distribution Path Optimization Problem Considering Carbon Emissions under Stochastic Demands

作　　者：刘丛贵 彭琨琨 邓旭东[1,2] 梅艳兰 刘翱 LIU Cong-gui;PENG Kun-kun;DENG Xu-dong;MEI Yan-lan;LIU Ao(School of Management,Wuhan University of Science and Technology,Wuhan 430065;State Key Laboratory of Intelligent Manufacturing Equipment and Technology,Huazhong University of Science and Technology,Wuhan 430074,China)

机构地区：[1]武汉科技大学管理学院,湖北武汉430065 [2]华中科技大学智能制造装备与技术全国重点实验室,湖北武汉430074

出　　处：《物流工程与管理》2024年第12期1-6,共6页Logistics Engineering and Management

基　　金：国家自然科学基金面上项目(52475526);智能制造装备与技术全国重点实验室开放课题资助项目(IMETKF2023028);湖北省自然科学基金面上项目(2021CFB368);湖北省高等学校优秀中青年科技创新团队计划项目(T2022003);武汉市知识创新专项项目(2023010201020407)。

摘　　要：目前随机需求下多温共配路径优化的相关研究较少,文中研究了随机需求下考虑碳排放的多温共配路径优化问题,并构建了数学模型,提出了基于蚁群算法的两阶段优化算法,以期提高多温共配效率,更好地应对客户的随机需求,降低碳排放。在数学模型中,配送总成本为优化目标,它综合考虑了车辆成本、保温箱成本、时间惩罚成本、碳排放成本以及路线的修正成本。在两阶段优化算法中,第一阶段设计了改进蚁群算法来获得优化的初始配送路线,第二阶段设计了基于混合规则的回程补货算法来对优化的初始配送路线进行修正。对比实验表明,改进蚁群算法和基于混合规则的回程补货算法是有效的,验证了两阶段优化算法的有效性。Relatively few studies have focused on the multi-temperature joint distribution path optimization problem under stochastic demands currently.In this paper,the multi-temperature joint distribution path optimization problem considering carbon emissions under stochastic demands is studied,corresponding mathematical model is constructed,and a two-stage optimization algorithm based on Ant Colony Optimization(ACO)is proposed to solve the problem,so as to enhance the multi-temperature joint distribution efficiency,cope better with the stochastic demands of customers,and reduce the carbon emissions.In the established mathematical model,the total distribution cost is utilized as the optimization objective,which includes the cost of vehicles,incubators,time penalties,carbon emissions,and route revision.In the proposed two-stage optimization algorithm,the first stage devises an improved ACO(IACO)algorithm to obtain an optimized initial distribution route,and then the second stage designs a mixed rule-based backhaul replenishment(MRBR)algorithm to revise the optimized distribution route obtained by the IACO.Comparison experiments have shown the proposed IACO and MRBR algorithm are efficient,which demonstrates the effectiveness of the proposed two-stage optimization algorithm.

关 键 词：多温共配路径优化 随机需求 蚁群算法 回程补货算法 碳排放 

分 类 号：U116.2[交通运输工程]