Abstract

Aiming at the problem of route optimization, a multi-objective optimized route distribution model is constructed with the goal of the smallest total transportation cost and the shortest total delivery route. In order to overcome the shortcomings of ant colony optimization, such as too long search time and easy to fall into local optimum, the ant colony pheromone volatilization coefficient is improved by the method of adaptive change value, which improves the adaptability of ant colony optimization. Therefore, the improved ant colony optimization is used to solve the logistics distribution route optimization problem. The experimental results show that the improved ant colony optimization can obtain a better logistics distribution route plan, which provides valuable reference information for improving the economic benefits of logistics enterprises.

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