Abstract

The purpose of this study is to generate efficient policies for the selection and postponement of copper sales contracts by a mining company. To do so, it uses a two-stage stochastic programming model that determines solutions considering different contract types, random prices, and risk aversion. The results show how it is possible for the selection to involve the lowest risk possible for different revenue levels required. During a period of high price volatility, an efficient solution may deliver an increase in monthly revenue of US$210,000 for a mining company that produces 50,000 tons per year, without any additional risk.