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Interior Optimization Methods constitute a practical contribution for Researchers, Postgraduates and MSc students to apply modern optimization techniques at any branch of Engineering and Natural Sciences. The mathematical basis is the theory of nonlinear systems of equations, which is applied on Graphical Optimization and software design. Any algorithm could be subject of Interior Optimization separation of variables to obtain a graphical optimization in a series of imaging processing steps with added numerical results. Advantages of this method are the easy and comparative results verification, got with imaging tools and numerical results at once. Engineering software knowledge is required to apply precisely these methods. Interior Optimization can be performed with any current scientific programming system able to combine numerical results with graphical solutions. For instance, but not limited to, Matlab, GNU-Octave, Freemat, Scilab and similar systems.