Multi-Agent Collaborative Task Planning with Uncertain Task Requirements

In response to the uncertainty of information of the injured in post disaster situations, considering constraints such as random chance and the quantity of rescue resource, the split delivery vehicle routing problem with stochastic demands (SDVRPSD) model and the multi-depot split delivery heterogeneous vehicle routing problem with stochastic demands (MDSDHVRPSD) model are established. A two-stage hybrid variable neighborhood tabu search algorithm is designed for unmanned vehicle task planning to minimize the path cost of rescue plans. Simulation experiments show that the solution obtained by the algorithm can effectively reduce the rescue vehicle path cost and the rescue task completion time, with high optimization quality and certain portability.