Discrete Optimization with Interval Data 53 hinsichtlich der zu verwendenden 'Oberga

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Discrete Optimization with Interval Data 53 hinsichtlich der zu verwendenden 'ObergaOperations research often solves deterministic optimization problems based on elegantand conciserepresentationswhereall parametersarepreciselyknown. In the face of uncertainty, probability theory is the traditional tool to be appealed for, and stochastic optimization is actually a signi? cant sub area in operations research. However, the systematic use of prescribed probability distributions so as to cope with imperfect data is partially