ABSTRACT
Optimization of mathematical functions is a process in which minimization and maximization of functions can be determined. This chapter uses a noncalculus approach to optimization theory of linear functions, an approach called linear programming. Using the calculus approach, several mathematical rules are available to optimize functions of one variable, of several variables, and of functions of several variables subject to constraints. In other words, the first type of optimization is called unconstrained optimization, whereas the second type is called constrained optimization. Take a mathematical function such as y = f(x), for which we want to find its optimum value. To find such a value, we differentiate the function and set its first derivative equal to zero.
