Abstract
Based on ant colony algorithm to solve the defect analysis of VRP problem, an adaptive dynamic search ant colony algorithm (ADACO) is proposed. Firstly, the model is established and the combination parameters is experimentally configured. Secondly, the strategy of combining pseudo-random and adaptive transition probability are used to help the group choose a higher quality path. When the group is in a local predicament, the segmented setting of the pheromone intensity induces the group to break out of the predicament in time. Finally, multiple groups of experimental tests are performed on the “Jia-hui Fresh” cargo delivery case. The results show that, compared with the original algorithm, the ADACO algorithm has respectively improved 17.65%, 16.13% and 16.10% in terms of delivery cost, convergence algebra and CPU running time.
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