A Modified Davidon-Fletcher-Powell Method for Solving Nonlinear Optimization Problems


  • Ali Joma'a Al-Issa Department of Mathematics, College of Computer Sciences and Mathematics University of Aleppo, Aleppo
  • Basim A. Hassan Department of Mathematics, College of Computers Sciences and Mathematics, University of Mosul, IRAQ
  • Issam A R Moghrabi 3Department of Computer Science, College of Arts and Sciences, University Central Asia, 310 Lenin Street, Naryn, 722918, Kyrgyz Republic https://orcid.org/0000-0002-4517-7630
  • Ibrahim M. Sulaiman Institute of Strategic Industrial Decision Modelling (ISIDM), School of Quantitative Sciences, Universiti Utara Malaysia, Sintok, 06010, Kedah, Malaysia https://orcid.org/0000-0001-5246-6636




Quasi-Newton Methods, Nonlinear optimization, Unconstrained optimization, DFP update


     One of the quasi-Newton update formulae, namely the Davidon-Fletcher-Powell method, is crucial for resolving nonlinear programming optimization problems. In order to achieve a Newton-like condition that depends on the function values and gradient vectors at each iteration, we construct an alternative positive-definite Hessian approximation in this study. The essential theorems are established to study algorithm convergence. The proposed approach is then tested on well-known test problems and then compared to the standard DFP method. The numerical outcomes demonstrate the effectiveness of the newly developed method.







How to Cite

A Modified Davidon-Fletcher-Powell Method for Solving Nonlinear Optimization Problems. (2024). Iraqi Journal of Science, 65(3), 1476-1484. https://doi.org/10.24996/ijs.2024.65.3.25

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