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This book presents the theory and methods of flexible and
generalized uncertainty optimization. Particularly, it describes
the theory of generalized uncertainty in the context of
optimization modeling. The book starts with an overview of flexible
and generalized uncertainty optimization. It covers uncertainties
that are both associated with lack of information and are more
general than stochastic theory, where well-defined distributions
are assumed. Starting from families of distributions that are
enclosed by upper and lower functions, the book presents
construction methods for obtaining flexible and generalized
uncertainty input data that can be used in a flexible and
generalized uncertainty optimization model. It then describes the
development of the associated optimization model in detail. Written
for graduate students and professionals in the broad field of
optimization and operations research, this second edition has been
revised and extended to include more worked examples and a section
on interval multi-objective mini-max regret theory along with its
solution method.
This book presents the theory and methods of flexible and
generalized uncertainty optimization. Particularly, it describes
the theory of generalized uncertainty in the context of
optimization modeling. The book starts with an overview of flexible
and generalized uncertainty optimization. It covers uncertainties
that are both associated with lack of information and are more
general than stochastic theory, where well-defined distributions
are assumed. Starting from families of distributions that are
enclosed by upper and lower functions, the book presents
construction methods for obtaining flexible and generalized
uncertainty input data that can be used in a flexible and
generalized uncertainty optimization model. It then describes the
development of the associated optimization model in detail. Written
for graduate students and professionals in the broad field of
optimization and operations research, this second edition has been
revised and extended to include more worked examples and a section
on interval multi-objective mini-max regret theory along with its
solution method.
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