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 ...

We present a mixed-integer nonlinear programming (MINLP) formulation of a UAV path optimization problem, and attempt to find the global optimum solution. As objective functions in UAV path ...

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 ...

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 ...

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

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) ...

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 ...

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) ...

Non-linear Programming Problem Solutions with MATLAB - proshir/Non-linear-Programming. Skip to content. Navigation Menu Toggle navigation. Sign in ... Each problem statement is accompanied by its ...

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) ...