Y. Qi, Yinuo Huang, Yuanyuan Ye, Wanli Wang, Yaping Fu, Kai Wang
{"title":"Multi-Objective Electric Truck Path Optimization Model with Time Window","authors":"Y. Qi, Yinuo Huang, Yuanyuan Ye, Wanli Wang, Yaping Fu, Kai Wang","doi":"10.1109/CRC.2019.00034","DOIUrl":null,"url":null,"abstract":"Aiming at the problem of electric truck path, an electric truck path optimization model with time window is proposed. The model considers the relationship between the speed of the electric truck, the load of the cargo, and the energy consumption, minimizing the total power consumption of the distribution center and the total advance or delay time. At the same time, simulation experiment is carried out by using the grey wolf algorithm. The comparison between the simulation results and the genetic algorithm shows that the grey wolf algorithm can solve the vehicle path planning with time window easily and effectively. It has better convergence and accuracy and is an effective way to solve such path optimization problems.","PeriodicalId":300065,"journal":{"name":"International Conference on Cybernetics, Robotics and Control","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Cybernetics, Robotics and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CRC.2019.00034","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Aiming at the problem of electric truck path, an electric truck path optimization model with time window is proposed. The model considers the relationship between the speed of the electric truck, the load of the cargo, and the energy consumption, minimizing the total power consumption of the distribution center and the total advance or delay time. At the same time, simulation experiment is carried out by using the grey wolf algorithm. The comparison between the simulation results and the genetic algorithm shows that the grey wolf algorithm can solve the vehicle path planning with time window easily and effectively. It has better convergence and accuracy and is an effective way to solve such path optimization problems.