A Region Enhanced Discrete Multi-Objective Fireworks Algorithm for Low-Carbon Vehicle Routing Problem  

作　　者：Xiaoning Shen Jiaqi Lu Xuan You Liyan Song Zhongpei Ge 

机构地区：[1]Collaborative Innovation Center of Atmospheric Environment and Equipment Technology,Jiangsu Key Laboratory of Big Data Analysis Technology,School of Automation,Nanjing University of Information Science and Technology,Nanjing 210044,China [2]School of Automation,Nanjing University of Information Science and Technology,Nanjing 210044,China [3]Institute of Trustworthy Autonomous Systems,and also with the Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation,Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen 518055,China

出　　处：《Complex System Modeling and Simulation》2022年第2期142-155,共14页复杂系统建模与仿真（英文）

基　　金：This work was supported by the Guangdong Provincial Key Laboratory(No.2020B121201001);the National Natural Science Foundation of China(NSFC)(Nos.61502239 and 62002148);Natural Science Foundation of Jiangsu Province of China(No.BK20150924);the Program for Guangdong Introducing Innovative and Enterpreneurial Teams(No.2017ZT07X386);Shenzhen Science and Technology Program(No.KQTD2016112514355531);Research Institute of Trustworthy Autonomous Systems(RITAS).

摘　　要：A constrained multi-objective optimization model for the low-carbon vehicle routing problem(VRP)is established.A carbon emission measurement method considering various practical factors is introduced.It minimizes both the total carbon emissions and the longest time consumed by the sub-tours,subject to the limited number of available vehicles.According to the characteristics of the model,a region enhanced discrete multi-objective fireworks algorithm is proposed.A partial mapping explosion operator,a hybrid mutation for adjusting the sub-tours,and an objective-driven extending search are designed,which aim to improve the convergence,diversity,and spread of the non-dominated solutions produced by the algorithm,respectively.Nine low-carbon VRP instances with different scales are used to verify the effectiveness of the new strategies.Furthermore,comparison results with four state-of-the-art algorithms indicate that the proposed algorithm has better performance of convergence and distribution on the low-carbon VRP.It provides a promising scalability to the problem size.

关 键 词：vehicle routing problem carbon emission multi-objective optimization fireworks algorithm region enhanced 

分 类 号：O17[理学—数学]