Robust optimization is a young and active research field that has been mainly developed in the last 15 years. Robust optimization is very useful for practice, since it is tailored to the information at hand, and it leads to computationally tractable formulations. It is therefore remarkable that real-life applications of robust optimization are still lagging behind; there is much more potential for real-life applications than has been exploited hitherto. The aim of this paper is to help practitioners to understand robust optimization and to successfully apply it in practice. We provide a brief introduction to robust optimization, and also describe important do׳s and don׳ts for using it in practice. We use many small examples to illustrate ou...
Robust optimization is a valuable alternative to stochastic programming, where all underlying probab...
Many real world optimization problems involve uncertainties. A solution for such a problem is expect...
Uncertain parameters appear in many optimization problems raised by real-world applications. To hand...
Robust optimization is a young and active research field that has been mainly developed in the last ...
Robust optimization (RO) is a young and active research field that has been mainly developed in the ...
Robust optimization is an emerging area in research that allows addressing different optimization pr...
In this paper we survey the primary research, both theoretical and applied, in the area of Robust Op...
In this paper we survey the primary research, both theoretical and applied, in the area of robust op...
Robust optimization is a young and emerging field of research having received a considerable increas...
We discuss the problem of evaluating a robust solution. To this end, we first give a short primer o...
Robust optimization is a methodology for dealing with uncertainty in optimization problems. In this ...
DoctoralThis is a two hours class on robust optimization. It starts with motivations and formulation...
Methods that use robust optimization are aimed at finding robustness to decision uncertainty. Uncert...
Robust optimization has become an important paradigm to deal with optimization under uncertainty. Ad...
Static robust optimization (RO) is a methodology to solve mathematical optimization problems with un...
Robust optimization is a valuable alternative to stochastic programming, where all underlying probab...
Many real world optimization problems involve uncertainties. A solution for such a problem is expect...
Uncertain parameters appear in many optimization problems raised by real-world applications. To hand...
Robust optimization is a young and active research field that has been mainly developed in the last ...
Robust optimization (RO) is a young and active research field that has been mainly developed in the ...
Robust optimization is an emerging area in research that allows addressing different optimization pr...
In this paper we survey the primary research, both theoretical and applied, in the area of Robust Op...
In this paper we survey the primary research, both theoretical and applied, in the area of robust op...
Robust optimization is a young and emerging field of research having received a considerable increas...
We discuss the problem of evaluating a robust solution. To this end, we first give a short primer o...
Robust optimization is a methodology for dealing with uncertainty in optimization problems. In this ...
DoctoralThis is a two hours class on robust optimization. It starts with motivations and formulation...
Methods that use robust optimization are aimed at finding robustness to decision uncertainty. Uncert...
Robust optimization has become an important paradigm to deal with optimization under uncertainty. Ad...
Static robust optimization (RO) is a methodology to solve mathematical optimization problems with un...
Robust optimization is a valuable alternative to stochastic programming, where all underlying probab...
Many real world optimization problems involve uncertainties. A solution for such a problem is expect...
Uncertain parameters appear in many optimization problems raised by real-world applications. To hand...