This chapter discusses basic optimization topics that are relevant to both linear and nonlinear problems. Sections 2.2-2.4 discuss local and global optima, convexity, and the general form of an optimization algorithm. These topics have traditionally been considered as fundamental topics in all areas of optimization. The later sections of the chapter, discussing rates of convergence, series approximations to nonlinear functions, and Newton's method for nonlinear equations, are most relevant to nonlinear optimization. In fact, Part II on linear programming can be understood without these later sections