Graphical optimization is a simple method for solving optimization problems involving one or two variables. For problems involving only one optimization variable, the minimum (or maximum) can be read simply from a graph of the objective function. For problems with two optimization variables, it is possible to obtain a solution by drawing contours of constraint functions and the objective function. The procedure is discussed in detail in the first section. After developing the procedure in detail with hand calculations, a Mathematica function called GraphicalSolution is presented that automates the process of generating the complete contour plots. The second section presents solutions of several optimization problems using this function.
KeywordsDust Mercury Covariance Cane Lution
Unable to display preview. Download preview PDF.