Forest fires are among the most frequent, intractable, and destructive natural disasters worldwide, inflicting profound ecological damage and posing grave threats to human life and property. To improve the autonomous decision making capabilities of unmanned intelligent systems in emergency rescue operations, this paper presents a mathematical model for coalition formation among heterogeneous firefighting resources. By implementing an optimized coalition structure, we streamline large scale organization and scheduling, accelerate analysis and decision making processes, and achieve the effective allocation of personnel, equipment, information, and other critical assets. Leveraging both Dutch and British auction mechanisms, we develop a multi round auction algorithm tailored to the diverse objectives and capabilities of intelligent agents within extensive forest firefighting scenarios, thereby improving task completion efficiency and resource utilization. Comparative simulation results demonstrate that our algorithm surpasses existing methods in metrics such as fire containment area, coalition stability, and overall response effectiveness. The methodology presented herein carries considerable practical significance: although designed for forest fire prevention and response, its underlying coalition formation and auction based resource allocation framework is readily generalizable to a range of large scale, complex task environments—such as industrial manufacturing, disaster relief, transportation logistics, and military operations—thereby furnishing a versatile paradigm for efficient system resource scheduling.

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