Formulating a nonlinear programming problem requires defining the decision variables and assigning them symbols, writing the objective function as a function of the decision variables (maximizing ...

Nonlinear programming (NLP) is a powerful technique for optimizing complex problems that involve nonlinear functions and constraints. However, choosing the best solver for your problem can be ...

Abstract: In this paper, we propose a trilinear optimization formulation and four mixed integer bilinear formulations to compute the Nash equilibria of a 2-player discounted stochastic game. The ...

An optimal placement of protective devices could increase the reliability and quality level of a distribution network. An innovative mixed-integer nonlinear programming model is proposed in this paper ...

The objective of this contribution is to propose a mixed integer nonlinear programming (MINLP) formulation for optimal design of a catalytic distillation column based on a generic nonequilibrium (NEQ) ...

Mixed-Integer Nonlinear Programming (MINLP): ... for iteratively adding linear constraints to an optimisation problem to eliminate infeasible regions and tighten the formulation.

A nonlinear programming formulation is introduced to solve infinite horizon dynamic programming problems. This extends the linear approach to dynamic programming by using ideas from approximation ...

In this study, an interval-parameter fuzzy robust nonlinear programming (IFRNP) model was developed for water quality management to deal with such difficulties. The developed model incorporated ...

Since acados mainly aims on providing SQP type methods for optimal control, it naturally needs optimal control structured nonlinear programming formulations (OCP-NLP) and quadratic programming (QP) ...

The objective of this contribution is to propose a mixed integer nonlinear programming (MINLP) formulation for optimal design of a catalytic distillation column based on a generic nonequilibrium (NEQ) ...