基于PSO的新算法在库存分类中的应用

Inventory classification using a new algorithm based on PSO algorithm

本文提出了基于粒子群(PSO)的训练ANN的新算法,以此为基础建立了对库存品进行ABC分类的模型。新算法充分结合了PSO与BP两者的优势,在训练过程中能同时优化权值以及神经元log-Sigmoid函数。实验结果表明,新算法是企业库存信息管理系统中进行决策预测的一种可行方法。

This paper presents a new ANN training algorithm based on PSO for ABC classification of stock keeping units （SKUs）. The new algorithm combines the strengths of BP training algorithm and PSO-Gain training algorithm; it can both optimize the weights of network and the log-sigmoid function of the network during the training process. The experiment results show that the new algorithm is a viable way for decision-making in information management system of enterprise inventory.