On distributionally robust joint chance-constrained problems
نویسندگان
چکیده
Introduction: A chance constrained optimization problem involves constraints with stochastic data that are required to be satisfied with a pre-specified probability. When the underlying distribution of the stochastic data is not known precisely, an often used model is to require the chance constraints to hold for all distributions in a given family. Such a problem is known as a distributionally robust chance constrained problem (DRCCP). We consider mixed integer linear DRCCP problems of the form:
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