Warehouse location optimization in fresh cold chain logistics based on PSO-GA

This study focuses on the site selection problem of fresh cold chain logistics warehouses, using a site selection model to minimize operating costs, improve distribution efficiency, and meet customer needs. The model covers warehouse location selection, special requirements for the fresh and cold chain, and organization of delivery routes. At the same time, a solution algorithm combining genetic algorithm and particle swarm optimization algorithm is proposed to solve the problem of location selection model. This hybrid algorithm encodes the layout problem of logistics points into a chromosome problem in genetic algorithms and utilizes particle swarm optimization to improve the efficiency of the search process and avoid early convergence difficulties. The results indicated that the improved algorithm was more effective than the ordinary genetic algorithm. After only 100 iterations, the objective function value of the algorithm decreased to approximately 31,500. The average total delivery cost of the model was reduced to 75.8369 million yuan, and the calculation was completed within 75 s, with significant efficiency. Therefore, this model can effectively assist logistics enterprises in accurately formulating economically effective distribution plans, achieving the optimal balance between cost and efficiency.