Add to ORKGRobustness is a very important concept present in diverse areas related to MCDM. In general words we can say that robustness is an attribute related to the “ability of a subject to cope well with uncertainties ” [8], more precisely the uncertainties that accompany the input of a system. In this work we are particularly interested in the concept of robust solution in optimisation an
Robust optimization is a young and active research field that has been mainly developed in the last ...
This paper considers the problem of robust optimization, and presents the technique called Robust Op...
Optimization is used for finding one or mo re optimal or feasible solutions for single and multiple ...
In real-world applications of optimization, optimal solutions are often of limited value, because di...
In the paper a new approach to goal programming is presented: the robust approach, applied so far to...
Practical optimization problems usually have multiple objectives, and they also involve uncertainty...
In design and optimization problems, a solution which is stable enough in its variability in presenc...
In optimization studies including multi-objective optimization, the main focus is placed on finding ...
Robust multi-objective optimization has emerged as an active research. A recent study proposed two d...
The question we address is how robust solutions react to changes in the uncertainty set. We prove th...
AbstractA robust optimization approach is proposed for generating nondominated robust solutions for ...
Engineering design often involves the optimization of different competing objectives. The aim is to ...
In optimization studies including multi-objective optimization, the main focus is usually placed in ...
In this thesis, several concepts of handling uncertainties in the formulation of mathematical optimi...
As an emerging research field, multiobjective robust optimization employs minmax robustness as the m...
Robust optimization is a young and active research field that has been mainly developed in the last ...
This paper considers the problem of robust optimization, and presents the technique called Robust Op...
Optimization is used for finding one or mo re optimal or feasible solutions for single and multiple ...
In real-world applications of optimization, optimal solutions are often of limited value, because di...
In the paper a new approach to goal programming is presented: the robust approach, applied so far to...
Practical optimization problems usually have multiple objectives, and they also involve uncertainty...
In design and optimization problems, a solution which is stable enough in its variability in presenc...
In optimization studies including multi-objective optimization, the main focus is placed on finding ...
Robust multi-objective optimization has emerged as an active research. A recent study proposed two d...
The question we address is how robust solutions react to changes in the uncertainty set. We prove th...
AbstractA robust optimization approach is proposed for generating nondominated robust solutions for ...
Engineering design often involves the optimization of different competing objectives. The aim is to ...
In optimization studies including multi-objective optimization, the main focus is usually placed in ...
In this thesis, several concepts of handling uncertainties in the formulation of mathematical optimi...
As an emerging research field, multiobjective robust optimization employs minmax robustness as the m...
Robust optimization is a young and active research field that has been mainly developed in the last ...
This paper considers the problem of robust optimization, and presents the technique called Robust Op...
Optimization is used for finding one or mo re optimal or feasible solutions for single and multiple ...