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Wildfires are natural disasters capable of damaging economies andcommunities. When wildfires become uncontrollable, Incident Manager Teams(IMT's) dispatch response vehicles to key assets to undertake protective tasksand so mitigate the risk to these assets. In developing a deployment plan undersevere time pressure, IMT's need to consider the special requirements of eachasset, the resources (vehicles and their teams), as well as uncertaintiesassociated with the wildfire. A common situation that arises in southernAustralian wildfires is a wind change. There is a reliable forecast of a windchange, but some uncertainty around the timing of that change. To assist IMT'sto deal with this situation we develop a two-stage stochastic model tointegrate such an uncertainty with the complexities of asset protectionoperations. This is the first time a mathematical model is proposed whichconsiders uncertainty in the timing of a scenario change. The model isimplemented for a case study that uses the context of the 2009 Black Saturdaybushfires in Victoria. A new set of benchmark instances is generated usingrealistic wildfire attributes to test the computational tractability of ourmodel and the results compared to a dynamic rerouting approach. Thecomputations reveal that, compared with dynamic rerouting, the new model cangenerate better deployment plans. The model can achieve solutions inoperational time for realistic-sized problems, although for larger problems thesub-optimal rerouting algorithm would still need to be deployed.

A two-stage stochastic approach for the asset protection problem during escaped wildfires with uncertain timing of a wind change