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 …

The inevitable presence of uncertain parameters in critical applications of process
optimization can lead to undesirable or infeasible solutions. For this reason, optimization …

Bilevel optimization problems are hierarchical optimization problems where the feasible
region of the so-called upper level problem is restricted by the graph of the solution set …

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

In multi-parametric programming an optimization problem is solved as a function of certain
parameters, where the parameters are commonly considered to be bounded and …

Abstract Machine learning-based model predictive control (ML-MPC) has been developed to
control nonlinear processes with unknown first-principles models. While ML models can …

In this paper we investigate multilevel programming problems with multiple followers in each
hierarchical decision level. It is known that such type of problems are highly non-convex and …

Funds from various global organizations, such as, The Global Fund, The World Bank, etc.
are not directly distributed to the targeted risk groups. Especially in the so-called third-world …

This book provides the fundamental underlying mathematical theory, numerical algorithms
and effi cient computational tools for the solution of multi-level mixedinteger optimization …

In this paper, the global and local optimal solutions of the linear trilevel programming
problem are concerned. First, we replace the lower level problem with its optimality …