FRACTIONAL ORDER LOG BARRIER INTERIOR POINT ALGORITHM FOR POLYNOMIAL REGRESSION IN THE ℓ p -NORM

Abstract

Fractional calculus is the branch of mathematics that studies the several possibilities of generalizing the derivative and integral of a function to noninteger order. Recent studies found in literature have confirmed the importance of fractional calculus for minimization problems. However, the study of fractional calculus in interior point methods for solving optimization problems is still new. In this study, inspired in applications of fractional calculus in many fields, was developed the so-called fractional order log barrier interior point algorithm by replacing some integer derivatives for the corresponding fractional ones on the first order optimality conditions of Karush-Kuhn-Tucker to solve polynomial regression models in the ℓ p −norm for 1 < p < 2. Finally, numerical experiments are performed to illustrate the proposed algorithm.