Title :
An Improved Genetic Algorithm for Vehicle Routing Problem with Time-Window
Author :
Wang, Wenfeng ; Wang, Zuntong ; Qiao, Fei
Author_Institution :
Coll. of Electron. & Inf. Eng., Tongji Univ., Shanghai, China
Abstract :
To overcome the common defects of early convergence in the existing genetic algorithm, an improved genetic algorithm with new crossover operator and new crossover strategy was presented for the solution to the vehicle routing problem with soft time window (VRPTW). Experiments show that the improved genetic algorithm can dramatically reduce the number of same or similar chromosomes, and increase the probability of finding the optimal solution as well as shorten the searching time, which is a really effective algorithm for VRPTW.
Keywords :
genetic algorithms; transportation; crossover operator; crossover strategy; genetic algorithm; searching time; soft time window; vehicle routing problem; Automobiles; Biological cells; Biological system modeling; Computer science; Encoding; Equations; Evolution (biology); Genetic algorithms; Routing; Vehicles; crossover operator; heuristic algorithm; the vehicle routing problem; time window;
Conference_Titel :
Computer Science and Computational Technology, 2008. ISCSCT '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3746-7
DOI :
10.1109/ISCSCT.2008.161
