This book examines optimization problems that in practice involve random model parameters. It details the computation of robust optimal solutions, i.e., optimal solutions that are insensitive with respect to random parameter variations, where appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into appropriate deterministic substitute problems.
Due to the probabilities and expectations involved, the book also shows...
This book examines optimization problems that in practice involve random model parameters. It details the computation of robust optimal solutions, ...
This book examines optimization problems that in practice involve random model parameters. It details the computation of robust optimal solutions, i.e., optimal solutions that are insensitive with respect to random parameter variations, where appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into appropriate deterministic substitute problems.
Due to the probabilities and expectations involved, the book also shows...
This book examines optimization problems that in practice involve random model parameters. It details the computation of robust optimal solutions, ...