Abstract: Using the traditional simulated annealing algorithm to solve complex nonlinear programming problems, there is a contradiction between cooling speed and solution quality, which can no longer meet the demand of fresh agricultural products distribution center site selection. To solve this problem, this paper designs a fresh agricultural products distribution center site selection method with improved simulated annealing algorithm, whose core idea is to fuse genetic algorithm with simulated annealing algorithm. Firstly, the chromosome individuals encoded by distribution center are introduced in the search link of the annealing process, and the chromosome sets that meet the conditions of the objective function parameters are screened, then the improved simulated annealing algorithm is applied to realize the overall optimization of the site selection process, and finally the simulation of the site selection problem of fresh agricultural products distribution center of company A in Shandong province is used. The experimental comparison results show that in multiple site selection process, the improved simulated annealing algorithm can effectively reduce the problem of large number of roundabout searches and invalid searches in the late stage of the traditional simulated annealing algorithm, and improve the efficiency of fresh agricultural products distribution center site selection.

Key words: distribution center site selection of fresh agricultural products, simulated annealing algorithm, genetic algorithm