Group Dispersed Heuristic Algorithm for Large Scale Multipoint Dynamic Aggregation Problem

This paper addresses the Large Scale Multipoint Dynamic Aggregation (MPDA) problem, a critical challenge in coordinating multiple agents for spatially and temporally dispersed tasks. We propose a novel centralized construction algorithm, the Group Dispersed Heuristic (GDH) algorithm, which leverages heuristic information and agent grouping to achieve rapid and effective solutions. The GDH algorithm is designed to minimize the completion time of the last task, considering the complex constraints and collaboration among agents. Through a comprehensive analysis of various state information and its impact on task execution, we provide an analytical basis for subsequent research. We also introduce a set of large-scale MPDA problem instances for algorithm performance evaluation. Experimental results demonstrate the superiority of the GDH algorithm over other construction algorithms, with significant reductions in makespan values across different difficulty levels. The GDH algorithm's adaptability in choosing between aggregation and distribution strategies based on task difficulty and status is highlighted as a key advantage. This research contributes to the field by offering a robust solution approach for large-scale MPDA problems and insights into heuristic algorithm design.