Title :
Improved Genetic Algorithm for Vehicle Routing Problem with Time Windows
Author_Institution :
Sch. of Bus. Adm., Nanchang Inst. of Technol., Nanchang, China
Abstract :
Vehicle routing problem with time windows (VRPTW) is a well-known and complex combinatorial problem, which has received considerable attention in recent years. In this paper, we propose an improved genetic algorithm to solve the VRPTW problem. The proposed approach, called IGA, employs two novel genetic operators. To verify the performance of IGA, we test it on six famous benchmark problems. Simulation results show that IGA outperforms other five compared algorithms on most test instances.
Keywords :
combinatorial mathematics; genetic algorithms; transportation; VRPTW; benchmark problems; complex combinatorial problem; genetic algorithm; vehicle routing problem with time windows; Benchmark testing; Genetic algorithms; Genetics; Optimization; Routing; Search problems; Vehicles; genetic algorithm; time window; vehicle routing problem;
Conference_Titel :
Intelligent Computing and Cognitive Informatics (ICICCI), 2010 International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-6640-5
Electronic_ISBN :
978-1-4244-6641-2
DOI :
10.1109/ICICCI.2010.42