Reverse Logistics Path Optimization Based on Hybrid Dung Beetle Optimization Algorithm - Xu, Xueguo; Yang, Chenzhao; Lei, Xue (International Journal of Industrial Engineering: Theory, Applications and Practice, 2025)
Reverse logistics optimization in urban environments faces significant challenges due to dispersed collection points and complex obstacle distributions, resulting in inefficient routing and high operational costs. To address these limitations, this study develops a novel hybrid optimization algorithm that strategically integrates Dung Beetle Optimization (DBO) with Simulated Annealing (SA) for multi-collector path planning. The hybrid approach enhances DBO's search capabilities by incorporating SA's probabilistic acceptance mechanism, effectively preventing premature convergence to suboptimal solutions. Using a two-dimensional grid model to represent urban collection environments, experimental validation demonstrates substantial performance improvements: the hybrid algorithm achieves 14.39% shorter paths than standalone DBO and 5.23% improvement over SA alone, while exhibiting faster convergence across diverse network configurations. These results confirm the method's effectiveness for sustainable reverse logistics operations in complex urban scenarios.