New Quasi-Newton (Dfp) With Logistic Mapping

Authors

  • Salah G. Shareef University of Zakho
  • Bayda G. Fathi University of Zakho

Keywords:

Unconstrained optimization, Quasi-Newton methods, DFP method, Logistic mapping

Abstract

In this paper, we propose a modification of the self-scaling quasi-Newton (DFP) method for unconstrained optimization using logistic mapping. We shoe that it produces a positive definite matrix. Numerical results demonstrate that the new algorithm is superior to standard DFP method with respect to the NOI and NOF.

Author Biographies

Salah G. Shareef, University of Zakho

Dept. of Mathematics, Faculty of Science, University of Zakho, Kurdistan Region-Iraq.

Bayda G. Fathi, University of Zakho

Dept. of Mathematics, Faculty of Science, University of Zakho, Kurdistan Region-Iraq.

References

Edwin, K. P. Chong and Stanislaw H. Zak: An Introduction To Optimization. Second Edition. John Wiley & Sons, Inc. United States of America, 2001.

Lu Hui-juan, ZHANG Huo-ming and MA Long-hua: A new optimization algorithm based on chaos. Journal of Zhejiang University SCIENCE A, 7(4), 2006.

Shanno, D. F. and Kettler, P. C.: Optimal Conditioning of Quasi- Newton methods. Mathematics of Computation. Volume 24, number 111, 1970.

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Published

2016-06-30

How to Cite

Shareef, S. G., & Fathi, B. G. (2016). New Quasi-Newton (Dfp) With Logistic Mapping. Science Journal of University of Zakho, 4(1), 115–120. Retrieved from https://sjuoz.uoz.edu.krd/index.php/sjuoz/article/view/312

Issue

Vol. 4 No. 1 (2016): June, 2016

Section

Science Journal of University of Zakho

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