关键词: 供应链网络, 变分不等式, 粒子群优化算法, 学习因子

Abstract: The traditional method of supply chain is projection, but it is very complex to calculate the projection. This paper presents an improved particle swarm algorithm to solve the problem of the supply chain network equilibrium. Constantly adjusting learning factor to balance the global exploring ability and the ability of local development of the algorithm improves optimization precision of algorithm. Through four numerical examples, and comparing with the standard particle swarm algorithm, artificial bee colony algorithm, and the particle swarm optimization algorithm with synchronous learning factor, the improved particle swarm optimization algorithm is proved to be effective and superior in solving the supply chain network equilibrium problem. It provides a new method for solving the supply chain network.

Key words: supply chains network, variational inequalities, particle swarm optimization, learning factor