| 生鲜电商配送的TDVRPTW研究: 基于经济成本与环境成本兼顾的视角 |
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| 引用本文： | 刘长石,周鲜成,盛虎宜,罗亮.生鲜电商配送的TDVRPTW研究: 基于经济成本与环境成本兼顾的视角[J].控制与决策,2020,35(5):1273-1280. |
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| 作者姓名： | 刘长石 周鲜成 盛虎宜 罗亮 |
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| 作者单位： | 湖南工商大学工商管理学院,长沙410205;湖南工商大学移动商务智能湖南省重点实验室,长沙410205;湖南工商大学移动商务智能湖南省重点实验室,长沙,410205;电子科技大学经济与管理学院,成都,611731 |
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| 基金项目： | 国家社科基金一般项目(17BJL091). |
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| 摘 要： | 基于经济成本与环境成本兼顾的视角,研究时变网络下生鲜电商配送的带时间窗车辆路径问题(TDVRPTW),综合考虑车辆时变行驶速度、车辆油耗、碳排放、生鲜农产品的易腐易损性、客户时间窗与最低新鲜度限制等因素,设计跨时间段的路段行驶时间计算方法,引入农产品新鲜度度量函数与碳排放率度量函数.在此基础上,以经济成本与环境成本之和最小为目标构建具有最低新鲜度限制的TDVRPTW数学模型,并根据模型特点设计一种自适应改进蚁群算法求解.最后采用案例验证所提出方法能有效规避交通拥堵时间段、降低总配送成本、促进物流配送领域的节能减排.
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| 关 键 词： | 时变网络 生鲜电商 新鲜度 碳排放 车辆路径问题 改进蚁群算法 |
TDVRPTW of fresh e-commerce distribution: Considering both economic cost and environmental cost |
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| LIU Chang-shi,ZHOU Xian-cheng,SHENG Hu-yi and LUO Liang.TDVRPTW of fresh e-commerce distribution: Considering both economic cost and environmental cost[J].Control and Decision,2020,35(5):1273-1280. |
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| Authors: | LIU Chang-shi ZHOU Xian-cheng SHENG Hu-yi and LUO Liang |
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| Affiliation: | School of Management,Hu''nan University of Business and Technology,Changsha410205,China;Key Laboratory of Hu''nan Province for Mobile Business Intelligence,Hu''nan University of Business and Technology,Changsha410205,China,Key Laboratory of Hu''nan Province for Mobile Business Intelligence,Hu''nan University of Business and Technology,Changsha410205,China,School of Economics and Management,University of Electronic Science and Technology of China,Chengdu 611731,China and Key Laboratory of Hu''nan Province for Mobile Business Intelligence,Hu''nan University of Business and Technology,Changsha410205,China |
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| Abstract: | The time-dependent vehicle routing problem with time windows (TDVRPTW) of fresh e-commerce distribution is studied by considering both economic cost and environmental cost. A calculation method for road travel time across time periods is designed. A freshness measure function of agricultural products and a measure function of carbon emission rate are employed by considering time-varying vehicle speeds, fuel consumptions, carbon emissions, perishable agricultural products, customers''time windows and minimum freshness. A TDVRPTW model is formulated with minimum freshness constraint. The object of the TDVRPTW model is to minimize the sum of economic cost and environmental cost. According to the characteristics of the model, an adaptive improved ant colony algorithm is designed. Finally, the experimental data show that the proposed approaches effectively avoid traffic congestions, reduce total distribution costs, and promote energy conservation and emission reduction. |
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