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Title
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A q-Fletcher-Reeves Conjugate Gradient Method for Unconstrained Optimization Problems
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Type
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Presentation
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Keywords
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Global optimization; q-calculus; q-gradient; Convergence; Mathenatical programming
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Abstract
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In this paper, we are concerned with the q-Fletcher-Reeves (q-FR) method for solving unconstrained optimization problems. The direction generated by the proposed method is a q-descent direction of the objective function which is computed using q-gradient. The q-gradient is a generalization of the classical gradient based on the q- derivative. Moreover, the q-FR method reduces to the classical version of FR method when q approaches 1. We prove that the proposed algorithm is globally convergent with the Armijo-type line search condition even if the objective function is nonconvex. Further, the numerical results show that the proposed method are very promising and competitive.
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Researchers
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Bhagwat Ram (Third Researcher), Mohammad Esmael Samei (Second Researcher), Shashi Kant Mishra (First Researcher)
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