Process Synthesis under Uncertainity via Multi-parametric Programming

Abstract In this work we propose a multi-parametric mixed-integer quadratic-approximation algorithm for the solution of convex multi-parametric mixed-integer nonlinear programming problems arising in process synthesis under uncertainty. The algorithm follows a decomposition procedure where a primal sub-problem is solved using multiparametric nonlinear programming techniques and a master sub-problem is solved using a mixed-inter-nonlinear programming formulation. An example problem is presented to illustrate the proposed algorithm.