Location Selection Strategy of Distribution Centers Based on Artificial Fish Swarm Algorithm Improved by Bacterial Colony Chemotaxis

Abstract

The distribution center (DC) is crucial in the connection between the suppliers and customers, thus the strategy for the selection and optimization of distribution center location plays an important role in logistics systems. In order to minimize the total cost, a distribution center location model with the lowest total cost is established. Accordingly, a distribution center location strategy based on artificial fish swarm algorithm improved by bacterial colony chemotaxis (BCC-AFSA) is proposed aiming to obtain a more feasible distribution center location strategy promptly. The algorithm of BCC- AFSA applies bacterial colony chemotaxis (BCC) to artificial fish swarm algorithm (AFSA) when the results do not change or change infinitesimally after multiple iterations. As result, the global optimization ability of the algorithm is improved. Through algorithm tests and example simulation, it is shown that the improved BCC- AFSA is more effective in the location selection strategy of distribution centers.