Mixed-integer polynomial programming (MIPP) problems are one class of mixed-integer nonlinear programming (MINLP) problems where objective function and constraints are restricted to the polynomial functions. Although the MINLP problem is NP-hard, in special cases such as MIPP problems, an efficient algorithm can be extended to solve it. In this research, we propose an algorit...

This article examines a new approach which solves Linear Programming (LP) problems with stochastic parameters as a generalized model of the fuzzy mathematical model analyzed by Verdegay. An expectation model is provided for solving the problem. A multi-parametric programming is applied to access to a solution with different desired degrees as well as problem constraints. Additionally, we presen...

An overview of multi-parametric programming and control is presented with emphasis on historical milestones, novel developments in the theory of multi-parametric programming and explicit MPC as well as their application to the design of advanced controller for complex multi-scale systems.

In this work, we present a new algorithm for solving complex multi-stage optimisation problems involving hard constraints and uncertainties, based on dynamic and multi-parametric programming. Each echelon of the dynamic programming procedure, typically employed in the context of multi-stage optimisation models, is interpreted as a robust multi-parametric optimisation problem, with the present s...

This work addresses the topic of constrained dynamic programming for problems involving multi-stage mixed-integer linear formulations with a linear objective function. It is shown that such problems may be decomposed into a series of multi-parametric mixed-integer linear problems, of lower dimensionality, that are sequentially solved to obtain the globally optimal solution of the original probl...

In this work, we present a new algorithm for solving complex multi-stage optimization problems involving hard constraints and uncertainties, based on dynamic and multi-parametric programming techniques. Each echelon of the dynamic programming procedure, typically employed in the context of multi-stage optimization models, is interpreted as a multi-parametric optimization problem, with the prese...