Linear and nonlinear programming are two types of optimization methods that can help you find the best solution to a problem involving decision variables, constraints, and an objective function.

In the context of my coursework for the Non-linear Programming course at university, I tackled various non-linear optimization problems using MATLAB. This project serves as a collection of my ...

Finally a short overview of relevant literature on algorithmic approaches for efficiently solving linear and nonlinear semidefinite programming is provided. Semidefinite programming (SDP) is one of ...

A nonlinear programming problem consists of four main elements: a decision variable vector, an objective function, a set of constraints, and a feasible region. The decision variable vector is a ...

Write down the Linear Program (LP ... To solve an Integer Programming problem, we can use the Branch and Bound algorithm: # IP: a minimization integer program with constraints and objective function ...

namely FWLP (Frank-Wolfe Linear Programming) and FWLP-P. The former iteratively applies the Frank-Wolfe algorithm to both the primal and dual of the saddle point formulation of a standard-form LP. The ...

However, QCOpt reformulates these non-linear constraints using well-known linearization techniques such that the resulting design problem is solved as a mixed-integer linear programming model. In this ...