This chapter introduces robust optimization (RO), where we aim to solve a MILO in which some of the parameters/data can take multiple (possibly infinitely many) values and we want the optimal solution to perform “the best possible,” assuming that the unknown problem parameters can always turn out to be “the worst possible.”
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