基于改进模拟退火算法的生鲜农产品配送中心选址

运用传统模拟退火算法解决复杂非线性规划问题，存在降温速度与求解质量之间的矛盾，已经不能满足生鲜农产品配送中心选址的需求。为解决这一问题，本文设计一种改进模拟退火算法的生鲜农产品配送中心选址方法。其核心思路是将遗传算法与模拟退火算法融合。首先在退火过程的搜索环节引入以配送中心为编码的染色体个体，并筛选出符合目标函数参数条件的染色体集;然后应用改进模拟退火算法实现选址过程的整体优化;最后采用山东省A公司生鲜农产品配送中心选址问题进行仿真模拟。实验对比结果表明，在多次选址求解过程中，改进模拟退火算法能有效减少传统模拟退火算法在运算后期大量迂回搜索、无效搜索的问题，提升生鲜农产品配送中心选址效率。

Distribution Center Site Selection of Fresh Agricultural ProductsBased on Improved Simulated Annealing Algorithm

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.