Scaled memoryless BFGS preconditioned steepest descent method for very large-scale unconstrained optimization
نویسندگان
چکیده
منابع مشابه
Scaled memoryless symmetric rank one method for large-scale optimization
This paper concerns the memoryless quasi-Newton method, that is precisely the quasi-Newton method for which the approximation to the inverse of Hessian, at each step, is updated from the identity matrix. Hence its search direction can be computed without the storage of matrices. In this paper, a scaled memoryless symmetric rank one (SR1) method for solving large-scale unconstrained optimization...
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ژورنال
عنوان ژورنال: Journal of Information and Optimization Sciences
سال: 2009
ISSN: 0252-2667,2169-0103
DOI: 10.1080/02522667.2009.10699885