Optimization in the design of fire weather monitoring networks

Abstract This paper discusses the development of two large-scale nonlinear optimization models, one stochastic and the other deterministic, for the optimal positioning of remote automatic weather stations (sensors) in an area of Southern California prone to forest fires. The requirements to implement the models under rather incomplete information are discussed and numerical results are presented which demonstrate the superiority of the stochastic model.