In multi-parametric programming, an optimization problem is solved for a range and as a
function of multiple parameters. In this review, we discuss the main developments of multi …

In this paper, we describe POP, a MATLAB toolbox for parametric optimization. It features (a)
efficient implementations of multiparametric programming problem solvers for …

This paper presents the concept of convex lifting, which will be proven to enable significant
implementation benefits for the class of piecewise affine controllers. Accordingly, two …

This work extends the theory of reciprocal diagrams in graphic statics to frameworks that are
invariant under finite group actions by utilizing the homology and representation theory of …

This paper studies generalized inverse reinforcement learning (GIRL) in Markov decision
processes (MDPs), that is, the problem of learning the basic components of an MDP given …

In 1864, JC Maxwell introduced a link between self-stressed frameworks in the plane and
piecewise linear liftings to 3-space. This connection has found numerous applications in …

This paper presents an efficient real-time implementation of embedded model predictive
control, adopted in the context of active vibration control with the objective of minimizing the …

This paper presents a new approach for control design of constrained linear systems
affected by bounded additive disturbances and polytopic uncertainties. This method hinges …

This paper demonstrates an efficient approach for the implementation of parametric
programming solutions to linear model predictive control problems. The emphasis is put …

Given a set of human's decisions that are observed, inverse optimization has been
developed and utilized to infer the underlying decision making problem. The majority of …