Emergency Disposal Resource Scheduling for Complex Operational Scenarios

In complex operational environments, the accumulation of a large number of materials, frequent equipment movement, and the complexity of processes, coupled with many unforeseen factors, can easily lead to emergencies, causing delays or interruptions to the original operation sequence. To effectively respond to emergencies, it is essential to quickly dispatch emergency resources to mitigate and eliminate their negative impact on the operational environment. However, during the emergency resource scheduling process, there are conflicts between the resource demands of the original tasks and those of the emergency response tasks, as well as the complexity of the environment and the uncertainty of its dynamic changes. In such a complex and ever-changing scenario, how to reasonably coordinate resource allocation, balance the efficiency of original operations with the speed of emergency response, and simultaneously adapt to the dynamic changes of the environment has become a key challenge in resource scheduling. To address this issue, this paper proposes a dynamic emergency resource scheduling algorithm, DEDRS, based on reinforcement learning and attention mechanisms, and through simulation experiments, the algorithm's significant advantages in overcoming dynamic environmental changes and optimizing resource allocation have been verified.