Design of Hybrid Optimization Algorithm Targeting at Vehicle Routing for Large-Scale Outlets

Sensors & Transducers

卷:165

Li Bo¹  Xu Shengzhou¹  Xu Ning²  Li Shen³  Li Yuan Xiang³ 

[1] Computer Science College, Central-South University for Nationalities, Wuhan, 430074, China;

[2] Computer Science College, Wuhan University of Technology, Wuhan, 430074, China ;

[3] Computer Science College, Wuhan University, Wuhan, 430074, China ;

关键词: Hybrid optimization;    Vehicle route planning;    Ant colony algorithm;    Genetic algorithm;    Chaos algorithm.;   

DOI  :  

来源: DOAJ

【 摘 要 】

Vehicle route planning is a NP-hard issue in logistics. This paper has designed a hybrid optimization algorithm based on ant colony algorithm, genetic algorithm and chaos algorithm to satisfy the large scale network requirements in practical applications. The innate advantages of the optimal route of ant colony algorithm has been fully used to establish good gene pool so as to take advantage of the genetic crossover and mutation of genetic algorithm and the randomness and ergodicity of chaos algorithm. Further optimization has been made to the individuals and populations of the ant colony algorithm and adaptive pheromone update mechanism has been established to effectively solve some practical problems concerning large-scale data file structure, such as the optimization, multiple time windows, line profile, and traffic impact and so on. A comparison of the efficiency of the algorithm shows that the algorithm proposed in the paper is of advantage in terms of time complexity and stability, which can effectively cope with large-scale data with over 1000 outlets, cater for other practical requirements and put into practical application.

【 授权许可】

Unknown