Using disjunctive programming to represent Risk Aversion policies
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We present a disjunctive programming approach to model risk aversion in the Brazilian Energy sector, and compare its performance with the traditional risk-averse approach using risk measures. We observe a better policy, with a more realistic representation of the decision maker’s preferences, and discuss the computational aspect of its implementation.