This paper introduces a method for computing the maximum volume inscribed ellipsoid and k-ball of a projected polytope. It is known that deriving an explicit description of a projected polytope is NP-hard. By using adjustable robust optimization techniques, we construct a computationally...

In this paper we propose a methodology for constructing decision rules for in-<br/>teger and continuous decision variables in multiperiod robust linear optimization<br/>problems. This type of problems finds application in, for example, inventory management, lot sizing, and manpower management. We show...

AMS classifications: 90D12, 90C05, 90C34.

Abstract: We propose a new way to derive tractable robust counterparts of a linear conic optimization problem by using the theory of Beck and Ben-Tal [2] on the duality between the robust (“pessimistic”) primal problem and its “optimistic” dual. First, we obtain a new convex...

Finding the lexicographic maximum of a polytope in Rn can be achieved by solving a suitable LP-problem.

This paper adresses the robust counterparts of optimization problems containing sums of maxima of linear functions and proposes several reformulations. These problems include many practical problems, e.g. problems with sums of absolute values, and arise when taking the robust counterpart of a...

Abstract: This paper determines the optimal timing of dike heightenings as well as the corresponding optimal dike heightenings to protect against floods. To derive the optimal policy we design an algorithm based on the Impulse Control Maximum Principle. In this way the paper presents one of the...

In this paper, a general method is described to determine uncertainty intervals for performance measures of Markov chains given an uncertainty region for the parameters of the Markov chains. We investigate the effects of uncertainties in the transition probabilities on the limiting...

AMS classifications: 65D05; 65K05; 90C22;

Abstract This article presents a novel combination of robust optimization developed in mathematical programming, and robust parameter design developed in statistical quality control. Robust parameter design uses metamodels estimated from experiments with both controllable and environmental...