TITLE:
A Review of Intelligent Optimization Algorithms in Supply Chain Networks
AUTHORS:
Nanlan Zhang, Fanrong Xie
KEYWORDS:
Supply Chain Networks, Intelligent Optimization Algorithm, Optimization Problem, Multi-Objective Optimization, Uncertainty Management
JOURNAL NAME:
Journal of Computer and Communications,
Vol.13 No.5,
May
14,
2025
ABSTRACT: Supply chain networks, which integrate nodes such as suppliers, manufacturers, and retailers to achieve efficient coordination and allocation of resources, serve as a critical component in enhancing corporate competitiveness. With the rapid advancement of artificial intelligence (AI) technologies, intelligent optimization algorithms have been increasingly applied in supply chain networks. This paper highlights classic algorithms such as genetic algorithm (GA), ant colony optimization (ACO), and particle swarm optimization (PSO), and expounds improved versions of these algorithms. By analyzing algorithmic enhancement strategies, including quantum GA, dynamic pheromone update mechanisms on ACO, and adaptive inertia weight adjustments on PSO, the development trends of intelligent optimization algorithms are outlined.