A Novel Supply Chain Multi-level Inventory Model based on Improved PSO Algorithm

Evolutionary algorithms and the intelligent optimization algorithms have achieved some research results, optimizing resource allocation and improving production efficiency in engineering design and everyday life. In this paper, by optimizing the traditional PSO algorithm, the novel supply chain multi-level inventory model is designed. In order to overcome the disadvantage of PSO (low robustness, complexity and time maladaptation), it is assumed that the particles in PSO are like electrons moving in the metal conductor in the external electric field, and the motion of the particles is the superposition of thermal motion and motion pointing to the optimal value of each particle. This is used to construct the novel PSO model. The algorithm is then applied to the supply chain network scheme. After testing under 100 and 1000 generations, the fitness value is calculated and proves the performance of the proposed method.