The goal of robust optimization problems is to find an optimal solution that is minimally sensitive to uncertain factors. Uncertain factors can include inputs to the problem such as parameters, decision variables, or both. Given any combination of possible uncertain factors, a solution is said to be robust if it is feasible and the variation in its objective function value is acceptable within ...

In this paper, we will discuss the use of new methods from robust control and especially H°° theory for the explicit construction optimal feedback compensators for several practical distributed parameter systems. Indeed, based on operator and interpolation theoretic methods one can now solve the standard H control problem for a broad class of systems modelled by PDEs. In our approach, the compl...

This paper proposes a robust model for optimizing collaborative reverse supply chains. The primary idea is to develop a collaborative framework that can achieve the best solutions in the uncertain environment. Firstly, we model the exact problem in the form of a mixed integer nonlinear programming. To regard uncertainty, the robust optimization is employed that searches for an optimum answer wi...