Research on Packing Problem Based on Improved Ant Colony Algorithm

This paper addresses the classical combinatorial optimization challenge of the packing problem by introducing an enhanced ant colony optimization (ACO) algorithm. Through a comprehensive analysis of the limitations inherent in traditional ACO approaches–particularly their slow convergence rates and susceptibility to local optima–we propose three key algorithmic improvements: an advanced pheromone update strategy, an optimized heuristic information design, and an innovative local search mechanism. Experimental evaluations demonstrate that our enhanced algorithm achieves significant improvements in both computational efficiency and solution quality, thereby offering a novel and effective methodology for tackling complex packing problems.