基于多智能体的网购生鲜无人车配送调度仿真  

Multi-agent Simulation for Online Fresh Food Autonomous Delivery

作　　者：陆淼嘉 黄承媛 滕靖[1] Lu Miaojia;Huang Chengyuan;Teng Jing(Tongji University,Shanghai 201804,China)

机构地区：[1]同济大学,上海201804

出　　处：《系统仿真学报》2022年第6期1185-1195,共11页Journal of System Simulation

基　　金：国家自然科学基金(72101188);上海市浦江人才计划(2020PJC112)。

摘　　要：无人车配送可有效缓解目前末端配送效率低、人力成本高、安全隐患多等问题。以城市社区网购生鲜无人车配送为研究对象,搭建了网购生鲜时空需求数据驱动的多智能体仿真平台,构建了基于实际路网的仿真环境及无人车、客户、配送站3类智能体,以运营成本最小及客户满意度最大为优化目标,设计并测试了动静态订单分配策略及距离最近或时间最紧配送路径规划策略。基于上海某生鲜电商实际订单数据,对不同策略展开情景模拟及敏感度分析,实现了运力资源的优化配置。Autonomous delivery can solve the last-mile delivery problems of low efficiency,high manual cost,and potential safety hazard.The autonomous delivery of the online fresh food in urban communities is discussed and a data-driven agent-based platform with the actual spatial-temporal demand is built.Three kinds of agents including the autonomous vehicles,customers,and distribution center and the simulation environment based on the actual road network are construct.To achieve the objectives of the minimum total operating costs and maximum customer satisfaction,the different static and dynamic order dispatch strategies and the route planning strategies with the principle of the closest and most urgent are designed and tested.Based on the real order data collected from a fresh food e-commerce platform in Shanghai,the scenario simulation and sensitivity analysis are conducted based on the different strategies to optimize the transport capacity resource of autonomous vehicle.

关 键 词：多智能体仿真 无人车配送 网购生鲜 订单分配 路径规划 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] U491[自动化与计算机技术—计算机科学与技术]