Abstract
This paper presents a Turbo-Basic program that implements a revised version of a new algorithm for the fast and optimum solution of the general linear minimax approximation problem. The algorithm proceeds iteratively and terminates when the global minimum value of the objective function is reached. The initial point may be selected arbitrarily or it may be optimally determined through a linear method to speed up algorithmic convergence. This algorithm is much faster and requires less storage than other approximation techniques. The program is implemented on an IBM-PC AT and tested by a number of approximation problems. Analytical examples are presented to illustrate how the program is used and the effectiveness of the algorithm.
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