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Improved genetic algorithm for vehicle routing problem with  hard time windows

WU Tian-yi,XU Ji-heng,LIU Jian-yong,ZAN Liang   

  1. College of Field Engineering, PLA University of Science and Technology, Nanjing 210007, China
  • Online:2014-04-24 Published:2010-01-03

Abstract: In view of the vehicle routing problem with hard time windows in military transportation, an improved genetic algorithm which aims to minimize the vehicles’total delivery time with the combination of hybrid crossover operation, improved mutation operation and an elite reserve strategy is put forward. First, it improves the initial population superiority by the greedy thought. Second, the entrance matrix and export matrix of the convergence population are constructed and the improved crossover operator based on the matrices is proposed. At the same time, the hybrid crossover operation is designed, which speeds up the population optimization through introducing the push forward insertion heuristic algorithm. At last, the population diversity is increased with the introduction of an improved mutation operator. The experimental results show that the improved genetic algorithm has a faster convergence speed and a better convergence effect than the basic algorithm.

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