Stochastic scheduling of single forest firefighting processor

Abstract

In forest firefighting, the longer the fires wait, the larger they grow and the longer they take to control. This study concerns the optimal deployment of single forest suppression processor of initial attack in the case of fires ignited simultaneously. The aim is to minimize the total damage caused by the fires to the burnt areas when all fires are suppressed. In Rachaniotis and Pappis (Can. J. For. Res. 36: 652–658, 2006), they use the concept of start-time dependent job processing times for modelling the time needed for fire suppression. The model is intricate but interesting in the sense that is based on theoretical and empirical research in the field of forest firefighting. As a continuation, a stochastic formulation that includes unpredicted parameters in the proposed model is considered and the “dynamic allocation index” rule is used to solve the problem. The optimality of this rule and its effectiveness are proven. Experimental results depict the framework, and inside it, the forest suppression processor achieves greater efficiency.