Plant Location Analysis Using Discrete Stochastic Programming

A plant location model with two major aspects is outlined. First, discrete stochastic programming is used to handle variability in supplies and demands. Second, the cost structure of plants is modelled in more detail and with more realism than is usual. Results from applying the model to the Queensland cattle slaughtering industry demonstrate the inappropriateness of using traditional deterministic plant location models to analyse problems with major stochastic elements. Deterministic models yield plant locations, sizes, throughputs, commodity flows and implications which differ markedly from those generated by stochastic models in which plant sizes and locations are optimally matched to variable fat cattle supplies. In addition, the traditional deterministic long-run model overestimates the normative gains of industry rationalisation.