New Direction in Derivative Free Optimization

Ahmed, Ahmed Mohamed Nageeb Alwasela; Supervisor, -Mohsin Hassan Abdalla Hashim

dc.contributor.author	Ahmed, Ahmed Mohamed Nageeb Alwasela
dc.contributor.author	Supervisor, -Mohsin Hassan Abdalla Hashim
dc.date.accessioned	2023-04-10T06:50:36Z
dc.date.available	2023-04-10T06:50:36Z
dc.date.issued	2023-01-19
dc.identifier.citation	Ahmed, Ahmed Mohamed Nageeb Alwasela . New Direction in Derivative Free Optimization \ Ahmed Mohamed Nageeb Alwasela ahmed ; Mohsin Hassan Abdalla Hashim .- Khartoum:Sudan University of Science and Technology,College of Science,2023.-105 p.:ill.;28cm.-Ph.D	en_US
dc.identifier.uri	https://repository.sustech.edu/handle/123456789/28359
dc.description	Thesis	en_US
dc.description.abstract	In this thesis, we study a derivative-free trust-region algorithm for large-scale unconstrained optimization, using symmetric-rank1 (SR1) to update the Hessian at every iteration. The centeral finite-difference iterations are used to approximate the gradient of the function. The iterative solution method and truncated Newton method were used to solve the trust-region sub-problem. Its performance is tested on some problems and compared the solutions found by truncated Newton method and iterative solution method.	en_US
dc.description.sponsorship	Sudan University of Science and Technology	en_US
dc.language.iso	en	en_US
dc.publisher	Sudan University of Science & Technology	en_US
dc.subject	Science	en_US
dc.subject	Mathematics	en_US
dc.subject	Derivative	en_US
dc.subject	Free Optimization	en_US
dc.title	New Direction in Derivative Free Optimization	en_US
dc.title.alternative	اتجاه جديد في الامثلية خالية المشتقة	en_US
dc.type	Thesis	en_US