A stochastic mixed-integer programming approach to optimal resource allocation for wildfire containment
Wildfires have been seriously threatening communities and our ecosystems in recent years. It is therefore imperative to deploy fire-fighting resources as early as possible before small fires become huge and destructive. This paper proposes a stochastic mixed-integer programming approach to the difficult problem of fire containment for initial attack. The problem involves determining the optimal mix of fire-fighting resources to contain a fire under uncertainty in fire evolution. Deterministic approaches assume that fire growth is known. However, in reality fire spread is uncertain and renders the deterministic models inadequate for this problem.
2006 IIE Annual Conference and Exhibition
author list (cited authors)
Ntaimo, L., Lee, W. J., & Jalora, A.
complete list of authors
Ntaimo, L||Lee, WJ||Jalora, A