Discrete Optimization with Interval Data - Minmax Regret and Fuzzy Approach Kasperski Adam Pevná vazba
Operations research often solves deterministic optimization problems based on elegantand conciserepresentationswhereall parametersarepreciselyknown. However, the systematic use of prescribed probability distributions so as to cope with imperfect data is partially unsatisfactory.… Celý popis ↓
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Discrete Optimization with Interval Data - Minmax Regret and Fuzzy Approach Kasperski Adam Pevná vazba
Operations research often solves deterministic optimization problems based on elegantand conciserepresentationswhereall parametersarepreciselyknown. However, the systematic use of prescribed probability distributions so as to cope with imperfect data is partially unsatisfactory. 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.
Agoodexampleiswhengoingfromdeterministictostoch- tic scheduling problems like PERT. First, going from a deterministic to a stochastic formulation, a problem may becomeintractable. From the inception of the PERT method in the 1950's, it was acknowledged that data concerning activity duration times is generally not perfectly known and the study of stochastic PERT was launched quite early.
Even if the power of today's computers enables the
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