Dealing with uncertainty is one of practical issues in design and operation of heat exchanger
networks (HENs), arising the problem of flexible HEN synthesis. This paper addresses the …

In this paper, model predictive control (MPC) based optimization problems with a quadratic
performance criterion and linear constraints are formulated as multi-parametric quadratic …

In this paper, we present an algorithm for the solution of multiparametric mixed integer linear
programming (mp-MILP) problems involving (i) 0-1 integer variables, and,(ii) more than one …

In this work we propose algorithms for the solution of multiparametric quadratic
programming (mp-QP) problems and multiparametric mixed-integer quadratic programming …

In this paper we present the main foundations and features of an integrated framework and
software platform that enables the use of model-based tools in design, operational …

In this paper, a stochastic programming framework is presented to address process
synthesis problems under uncertainty. The framework is based on a two-state stochastic …

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

In this paper, a parametric programming approach is proposed for the analysis of linear
process engineering problems under uncertainty. A novel branch and bound algorithm is …

In this paper we present novel theoretical and algorithmic developments for the solution of
mixed-integer optimization problems involving uncertainty, which can be posed as …

A systematic procedure proposed here selects optimal solvent blends for nonreactive,
multicomponent absorption processes accounting for plant‐wide point source environmental …