Method and System for Collaborative Schedule of Supply Chain Production and Transportation Based on Improve Particle Swarm Optimization Algorithm

In the traditional supply chain management methods, the collaborative scheduling decisions of supply chain production and transportation are independent of each other, and their coordination is often ignored. Independent production scheduling decision and distribution scheduling decision can not make the operation level of supply chain optimal, especially in the supply chain system with very limited transportation resources. In this paper, the improved PSO(Particle swarm optimization) algorithm is applied to optimize the collaborative scheduling problem of production and transportation in supply chain. Combining the strong global search ability of GA(genetic algorithm) and the fast convergence speed of PSO algorithm, a hybrid algorithm is constructed by complementing each other's advantages. The research results show that the hybrid algorithm has better optimization performance, which proves that the hybrid algorithm has better performance, and has the advantages of fast convergence speed of PSO algorithm and strong global search ability of GA. It can effectively solve the problem of collaborative scheduling of production and transportation in supply chain.