  Unmanned warehouses are an important part of logistics, and improving their
operational efficiency can effectively enhance service efficiency. However, due
to the complexity of unmanned warehouse systems and their susceptibility to
errors, incidents may occur during their operation, most often in inbound and
outbound operations, which can decrease operational efficiency. Hence it is
crucial to to improve the response to such incidents. This paper proposes a
collaborative optimization algorithm for emergent incident response based on
Safe-MADDPG. To meet safety requirements during emergent incident response, we
investigated the intrinsic hidden relationships between various factors. By
obtaining constraint information of agents during the emergent incident
response process and of the dynamic environment of unmanned warehouses on
agents, the algorithm reduces safety risks and avoids the occurrence of chain
accidents; this enables an unmanned system to complete emergent incident
response tasks and achieve its optimization objectives: (1) minimizing the
losses caused by emergent incidents; and (2) maximizing the operational
efficiency of inbound and outbound operations during the response process. A
series of experiments conducted in a simulated unmanned warehouse scenario
demonstrate the effectiveness of the proposed method.
