Exploring Hybrid Genetic Algorithm Based Large-Scale Logistics Distribution for BBG Supermarket  

作　　者：Yizhi Liu Rutian Qing Liangran Wu Min Liu Zhuhua Liao Yijiang Zhao 

机构地区：[1]Key Laboratory of Knowledge Processing and Networked Manufacturing,College of Hunan Province,Xiangtan,411201,China [2]School of Computer Science and Engineering,Hunan University of Science and Technology,Xiangtan,411201,China

出　　处：《Journal on Artificial Intelligence》2021年第1期33-43,共11页人工智能杂志（英文）

基　　金：This project was funded by the National Natural Science Foundation of China(41871320,61872139);the Provincial and Municipal Joint Fund of Hunan Provincial Natural Science Foundation of China(2018JJ4052);Hunan Provincial Natural Science Foundation of China(2017JJ2081);the Key Project of Hunan Provincial Education Department(19A172);the Scientific Research Fund of Hunan Provincial Education Department(18K060).

摘　　要：In the large-scale logistics distribution of single logistic center,the method based on traditional genetic algorithm is slow in evolution and easy to fall into the local optimal solution.Addressing at this issue,we propose a novel approach of exploring hybrid genetic algorithm based large-scale logistic distribution for BBG supermarket.We integrate greedy algorithm and hillclimbing algorithm into genetic algorithm.Greedy algorithm is applied to initialize the population,and then hill-climbing algorithm is used to optimize individuals in each generation after selection,crossover and mutation.Our approach is evaluated on the dataset of BBG Supermarket which is one of the top 10 supermarkets in China.Experimental results show that our method outperforms some other methods in the field.

关 键 词：Large-scale logistics distribution vehicle routing greedy algorithm hill-climbing algorithm hybrid genetic algorithm 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]