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.

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 ...

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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 ...

This paper presents two different formulations of optimal PMU placement (OPP) problem: mixed integer linear programming (MILP) and nonlinear programming (NLP). For each formulation, modeling of power ...

changes nonlinear system to an equivalent linear system, in the second phase, using discretization method, the attained problem is converted to a linear programming problem, and in the third phase, ...

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 ...

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 ...