A Nonmonotone Conjugate Residual SR۱-Trust Region-Line Search Algorithm for Large Scale Unconstrained Optimization
Publish Year: 1402
نوع سند: مقاله کنفرانسی
زبان: English
View: 66
متن کامل این Paper منتشر نشده است و فقط به صورت چکیده یا چکیده مبسوط در پایگاه موجود می باشد.
توضیح: معمولا کلیه مقالاتی که کمتر از ۵ صفحه باشند در پایگاه سیویلیکا اصل Paper (فول تکست) محسوب نمی شوند و فقط کاربران عضو بدون کسر اعتبار می توانند فایل آنها را دریافت نمایند.
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
ICIORS16_107
تاریخ نمایه سازی: 2 اسفند 1402
Abstract:
Here, we present a new nonmonotone trust region-line search algorithm for solving large scale unconstrained optimization. At each iteration of our algorithm, the trust region subproblem is solved by a truncated conjugate residual (CR) method to obtain a step direction. Our new nonmonotone algorithm allows accepting a specified maximum number of consecutive “failed” iterations. When the number of consecutive failed iterations exceeds a specified limit, a backtracking line search process is used to obtain a sufficient reduction in the objective function. In fact, our proposed nonmonotone algorithm avoids resolving the trust region subproblem in the face of a failed iteration. Moreover, the symmetric rank one updating strategy is used to update the Hessian matrix approximation. Preliminary numerical results of an implementation of the proposed algorithm on some test problems from CUTEst library confirm the efficiency and robustness of the algorithm.
Keywords:
Unconstrained Optimization , Quasi-Newton Method , Symmetric Rank One Update , Nonmonotone Method , Conjugate Residual.
Authors
Hani Ahmadzadeh
Department of Mathematical Sciences, Sharif University of Technology, Tehran, Iran
Nezam Mahdavi-Amiri
Department of Mathematical Sciences, Sharif University of Technology, Tehran, Iran
Maryam Siyadatiy
Department of Mathematical Sciences, Sharif University of Technology, Tehran, Iran