Towards a Discrete Newton Method with Memory for Large-scale Optimization 1 By
نویسندگان
چکیده
A new method for solving large nonlinear optimization problems is outlined. It attempts to combine the best properties of the discrete-truncated Newton method and the limited memory BFGS method, to produce an algorithm that is both economical and capable of handling ill-conditioned problems. The key idea is to use the curvature information generated during the computation of the discrete Newton step to improve the limited memory BFGS approximations. The numerical performance of the new method is studied using a family of functions whose nonlinearity and condition number can be controlled.
منابع مشابه
A limited memory adaptive trust-region approach for large-scale unconstrained optimization
This study concerns with a trust-region-based method for solving unconstrained optimization problems. The approach takes the advantages of the compact limited memory BFGS updating formula together with an appropriate adaptive radius strategy. In our approach, the adaptive technique leads us to decrease the number of subproblems solving, while utilizing the structure of limited memory quasi-Newt...
متن کاملOptimization Technology Center towards a Discrete Newton Method with Memory for Large Scale Optimization
A new method for solving large nonlinear optimization problems is outlined It attempts to combine the best properties of the discrete truncated Newton method and the limited memory BFGS method to produce an algorithm that is both economical and capable of handling ill conditioned problems The key idea is to use the curvature information generated during the computation of the discrete Newton st...
متن کاملTowards a Discrete Newton Method with Memory for Large-scale Optimization
A new method for solving large nonlinear optimization problems is outlined. It attempts to combine the best properties of the discrete-truncated Newton method and the limited memory BFGS method, to produce an algorithm that is both economical and capable of handling ill-conditioned problems. The key idea is to use the curvature information generated during the computation of the discrete Newton...
متن کاملTitle: towards a Discrete Newton Method with Memory for Large-scale Optimization
A new method for solving large nonlinear optimization problems is outlined. It attempts to combine the best properties of the discrete-truncated Newton method and the limited memory BFGS method, to produce an algorithm that is both economical and capable of handling ill-conditioned problems. The key idea is to use the curvature information generated during the computation of the discrete Newton...
متن کاملSIZING OPTIMIZATION OF TRUSS STRUCTURES WITH NEWTON META-HEURISTIC ALGORITHM
This study is devoted to discrete sizing optimization of truss structures employing an efficient discrete evolutionary meta-heuristic algorithm which uses the Newton gradient-based method as its updating scheme and it is named here as Newton Meta-heuristic Algorithm (NMA). In order to enable the NMA population-based meta-heuristic to effectively explore the discrete design space, a term contain...
متن کامل