Algorithms for minimax and expected value optimization

Many decision models can be formulated as continuous minimax problems. The minimax framework injects robustness into the model. It is a tool that one can use to perform worst–case analysis, and it can provide considerable insight into the decision process. It is frequently used alongside other methods such as expected value optimization in order to identify extreme scenarios and strategies that might provide cover under such scenarios. Despite its importance and usefulness, there are very few algorithms that can reliably solve continuous minimax problems. In this chapter we will describe algorithms for the solution of such problems.