基于增强学习的农产品物流路径选择方案

The Scheme of Route Selection of Agricultural Products Logistics Based on Enhanced Learning

针对农产品物流问题,首先,提出了一种基于模糊增强学习算法的路径选择方案.该算法具有独立的模糊规则结构调整模块,采用模糊规则来逼近值函数,以提高增强学习算法的性能.然后,将该算法应用于一个简单的农产品物流场景,以解决农产品的库存控制问题.农产品供应商在考虑其有限的供应能力,根据效用来确定每个零售商的订单数量.最后,通过仿真实验来验证该算法的有效性.

Firstly, aiming at the problem of agricultural product logistics, a route selection scheme based on fuzzy enhanced learning algorithm is proposed. The algorithm has an independent structure adjustment module of fuzzy rules, and uses fuzzy rules to approximate the value function to improve the performance of the learning algorithm. Then, the algorithm is applied to a simple agricultural product logistics scenario to solve the inventory control problem of agricultural products. Agricultural suppliers consider their limited supply capacity and determine the order quantity of each retailer according to their effectiveness. Finally, the effectiveness of the algorithm is verified by simulation experiments.