基于配送收益均衡的多目标绿色车辆路径优化算法
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作者单位:

江苏海洋大学

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中图分类号:

TP18

基金项目:

国家自然科学基金项目(61873105);江苏省青蓝工程中青年学术带头人;连云港市海燕计划;江苏省科研与实践创新计划项目(KYCX20_2936)


A Multi-objective Green Vehicle Routing Optimization Algorithm based on Delivery Benefit Balance
Author:
Affiliation:

Jiangsu Ocean University

Fund Project:

The National Natural Science Foundation of China (61873105);Young and middle-aged academic leader of Jiangsu Qinglan Project; Lianyungang Haiyan Project;Jiangsu Province Scientific Research and Practice Innovation Project(KYCX20_2936)

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    摘要:

    为满足电商平台减少物流成本和人力成本的需求,提高车辆配送效率,降低碳排放量,实现低碳绿色 出行,本文研究配送收益均衡的多目标绿色车辆路径问题及其智能求解算法。首先,以最小化燃油消耗量、基 于客户满意度的惩罚成本和配送收益方差为目标建立多目标绿色车辆路径模型;然后,将变邻域搜索算子融 入NSGA-II算法中, 设计求解上述模型的多目标进化优化算法; 最后, 通过在18个测试数据集上与2个模型 和3种算法的对比,验证了所提模型的可行性和算法的有效性。

    Abstract:

    In order to meet the needs of reducing transportation and labor costs for the e-commerce platform,improve vehicle delivery efficiency,reduce carbon emissions,and achieve low-carbon green travel,a delivery benefit balance-based green vehicle routing problems and its intelligent solving algorithm are focused in this paper.First,a multi-objective green vehicle routing model is established to minimize fuel consumption,penalty cost based on the customer’s satisfaction and the variance of the delivery benefits;after that,a multi-objective evolutionary algorithm is developed to solve the above model by integrating variable neighborhood search operators into NSGA-II;finally,the comparison with two models and three algorithms on eighteen benchmark data-sets validates the feasibility of the model and the efficiency of the solving algorithm.

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历史
  • 收稿日期:2021-04-19
  • 最后修改日期:2022-05-25
  • 录用日期:2021-10-27
  • 在线发布日期: 2021-12-01
  • 出版日期: