ABSTRACT
The one-dimensional (1-D) optimization problem refers to an objective function with one variable. In practice, optimization problems with many variables are complex, and rarely does one find a problem with a single variable. However, 1-D optimization algorithms form the basic building blocks for multivariable algorithms. As these algorithms form a subproblem of multivariable optimization problems, numerous methods (or algorithms) have been reported in the literature, each with some unique advantage over the others. These algorithms are classified into gradient-based and non-gradientbased algorithms. Some popular algorithms are discussed in this chapter.
