Research on multi-channel pricing decision of cluster supply chain

With changes in the social and economic environment, more and more small and medium-sized enterprises gather in the supply chain to form industrial clusters. How to customize reasonable prices and maximize the profit of products in cluster supply chain has become an important research topic. This paper is based on the clustering supply chain pricing strategy, mathematical modeling based on the pricing model of Mukhopadhyay economics, and then, the collaborative decision-making algorithm based on the double-layer adaptive genetic algorithm and particle swarm optimization algorithm is used to study the pricing scheme which can ensure the maximum profit of each supply chain and the total profit of the whole cluster supply chain. And study the impact on the optimization plan when consumer preferences change and the price elasticity of demand changes. It can be seen from the experimental results that this research has certain reference value for seeking optimal pricing for cluster supply chains.