Some Topics on Convex Optimization
Abbas Musleh Salman1*, Ahmed ALRIDHA2, Ahmed Hadi Hussain3
1,2University of Babylon / College of Education for Pure Sciences
3University of Babylon / College of Engineering Al-Musayab
Emails: abbas.mmm2019@gmail.com
amqa92@yahoo.com
met.ahmed.hadi@uobabylon.edu.iq
Abstract. The aim of this paper is to clarify several important points, including a brief and
adequate explanation of loving improvement, as well as laying out a number of important
mathematical formulas that we need, supported with graphs.
1. Introduction
Each sub-field of mathematical optimization can be called a convex optimization and a sub-field gap
that addresses and studies the problem of reducing convex functions on other convex groups
alike.Likewise, There are many classes and classes of convex improvement problems accept polynomial
mathematical algorithms and formulas, [1] while mathematical optimization is generally a problem or
problem of difficulty to solve, which is one of the difficult NP problems, [1] [2] [3]. The problem of
these systems can only be solved directly by approximation and finding the result by estimation,
estimation .It also has a number of applications, including signal processing, communications and
offices of all kinds, design of private electronic circuits, [3] and its uses also include information
investigation and demonstrating, self-financing, measurements (ideal test plan), [3] and basic
improvement, where the idea of approximation has proven its high effectiveness. [2], [3] With late
advances in figuring calculations and improvement, so curved programming has become nearly as clear
as straight programming.