Abstract
A modified flexible tolerance method for nonlinear optimization is presented. The modification incorporates a random search technique with the flexible tolerance method, making the flexible tolerance method more efficient and effective. Test problems of nonlinear programming algorithms presented by previous investigators are included to illustrate the advantages of the modified method
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