In this paper, the optimizations problems to seek robust solutions under uncertainty are considered. The light robust approach is one of the strong and new methods to achieve robust solutions under conditions of uncertainty. In this paper, we tried to improve the quality of the solutions obtained from the Light Robust method by introducing a revised approach. Considering the problem concerned, ...

This paper presents a general model for unification of the robust counterparts of uncertain linear programs (LP). We extend the robust optimization methodology for LP, introduced by Ben-Tal and Nemirovski, to a unified model in which the uncertainty region is approximated by an appropriate norm body. We derive the robust counterpart of an LP whose parameters may fall in any of the ∞ l l l , , 2...

Of interest here are linear data fitting problems with uncertain data which lie in a given uncertainty set. A robust counterpart of such a problem may be interpreted as the problem of finding a solution which is best over all possible perturbations of the data which lie in the set. In particular, robust counterparts of total least squares problems have been studied and good algorithms are avail...

The problems of non-normality or functional relationships between variables may often be simplified by an appropriate transformation. However, the evidence for transformations may sometimes depend crucially on one or a few observations. Therefore, the purpose of the paper is to develop a method that will not be influenced by potential outliers during the process of data transformations. The con...

We address bilevel programming problems when the derivatives of both the upper and the lower level objective functions are unavailable. The core algorithms used for both levels are trust-region interpolation-based methods, using minimum Frobenius norm quadratic models when the number of points is smaller than the number of basis components. We take advantage of the problem structure to derive c...

In this study, we propose a robust bi-objective optimization model of the green closed-loop supply chain network considering presorting, heterogeneous transportation system, and carbon emissions. The proposed is an uncertain mixed-integer linear that maximizes profit minimizes emissions by costs, selling price, approach implemented using combined interval polyhedral, “Interval+ Polyhedral,” unc...