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Physical Sciences and Mathematics Commons

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Computer Engineering

2024

Vehicle routing problem

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

Research Advances On Electric Vehicle Routing Problem Models And Algorithms, Helin Zhuang, Xiaoyun Xia, Kangshun Li, Zefeng Chen, Xianchao Zhang Feb 2024

Research Advances On Electric Vehicle Routing Problem Models And Algorithms, Helin Zhuang, Xiaoyun Xia, Kangshun Li, Zefeng Chen, Xianchao Zhang

Journal of System Simulation

Abstract: The development of electric vehicle provides an alternative to conventional fuel vehicles for logistics companies. Using electric vehicles has the merits of less pollution and low noise, but the characteristics of limited cruising range and limited number of charging stations are new challenges. Electric vehicle routing problems(EVRPs) have been widely used in transportation, logistics and other fields, and have received much attention. A comprehensive survey of EVRP and its many variants are presented and the respective backgrounds and applicable conditions are analyzed. The solving approaches of EVRPs are categorized, the strengths and weaknesses of each algorithm are analyzed, and …


Emergency Material Scheduling Based On Discrete Shuffled Frog Leaping Algorithm, Xiaoning Shen, Zhongpei Ge, Chengbin Yao, Liyan Song, Yufang Wang Jan 2024

Emergency Material Scheduling Based On Discrete Shuffled Frog Leaping Algorithm, Xiaoning Shen, Zhongpei Ge, Chengbin Yao, Liyan Song, Yufang Wang

Journal of System Simulation

Abstract: A mathematical model of emergency material scheduling after earthquakes is built. The model evaluates the emergency degree of each disaster area based on the disaster situation and designs a method to split the demand of the disaster area, improving the efficiency of vehicle utilization. To solve the model, this paper proposes a discrete shuffled frog leaping algorithm with multi-resource learning. The multiple information sources introduced by the proposed algorithm can expand the search direction and reduce the assimilation speed of the population in the algorithm. Second, the worst individual in each subgroup can learn the effective information in the …