Research On Multi-level Supply Chain Inventory Optimization Based On Particle Swarm Optimization Algorithm
Wang Yan1  Yong Chaokang2

1 Chengdu Industry & Trade College，Chengdu Sichuan,611731;

2 Sichuan Traffic Technician College,Chengdu Sichuan,611130;

Abstract: In the context of global digitalization and intelligent transformation, supply chain management is undergoing fundamental restructuring. Within multi-level supply chain systems, traditional inventory control strategies often fail to achieve overall system optimization due to challenges such as numerous nodes, information transmission delays, and amplification of prediction errors. Particle Swarm Optimization (PSO), a representative swarm intelligence optimization method, has gained widespread application in solving complex constraint-based and multi-variable interactive problems through its structural simplicity and high search efficiency. This study focuses on multi-level supply chain inventory optimization by developing a collaborative model involving suppliers, manufacturers, distributors, and retailers. An enhanced PSO optimization strategy is proposed, incorporating dynamic inertia weights, local fine-grained search, and multi-objective fitness functions to significantly improve convergence efficiency and robustness in multi-level supply chain inventory optimization.

Key words: Multi-level Supply Chain; Inventory Optimization; Improved PSO Algorithm

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