An improved adaptive genetic algorithm for vehicle routing problem

In order to solve the problem of slow convergence speed of adaptive genetic algorithm (AGA) in the early stage of evolution, an improved adaptive genetic algorithm (IAGA) was presented. With the introduction of an indicator evaluating the degree of population diversity, the new algorithm can adaptively adjust the probabilities of crossover. Furthermore, the IAGA was applied to vehicle routing problem. The experimental results demonstrate that the new algorithm can effectively improve convergence speed compared to the AGA and the optimal or nearly optimal solutions to the vehicle routing problem can be easily obtained.