Enhanced Gold Mining Optimization with Dual-Layer Information Sharing and Dynamic Control for Multi-Objective Scheduling of Heterogeneous UAV Swarms
This paper proposes an Improved Gold Mine Optimization Algorithm with a dual-layer information-sharing framework and dynamic Pareto dominance (IGMO-DP) to effectively solve the multi-objective scheduling problem of heterogeneous UAV swarms by simultaneously optimizing mission completion time, energy consumption, and load balance, demonstrating superior convergence and solution diversity compared to state-of-the-art algorithms.