Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: , a new inexact line search rule is presented for solving a class of fundamental unconstrained optimisation problems. As a modified version of the standard Armijo line search rule, it incorporates the information of the second order derivative of objective function into determining a suitable step length based on the more accurate approximation of objective function. Owing to this line search, a greater reduction of objective function may be obtained at each iteration as ll as with less cost of computation. Combined with a choice of descent search direction, a ll defined algorithm is developed, where the line search rule allows the initial step length to be adjusted automatically such that the numerical performance of algorithm is improved. Under some mild assumptions, global convergence is established for the algorithm. Numerical results demonstrate that the proposed method is promising, especially in comparison with the existing methods.
['Zhong Wan', 'Yu Chen', 'Xiaodong Zheng']
I am writing a research paper on a idea Solution method of optimisation problem based on a modified Armijo-type line search
[{"from": "human", "value": "I am writing a research paper on a idea Solution method of optimisation problem based on a modified Armijo-type line search"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: , a new inexact line search rule is presented for solving a class of fundamental unconstrained optimisation problems. As a modified version of the standard Armijo line search rule, it incorporates the information of the second order derivative of objective function into determining a suitable step length based on the more accurate approximation of objective function. Owing to this line search, a greater reduction of objective function may be obtained at each iteration as ll as with less cost of computation. Combined with a choice of descent search direction, a ll defined algorithm is developed, where the line search rule allows the initial step length to be adjusted automatically such that the numerical performance of algorithm is improved. Under some mild assumptions, global convergence is established for the algorithm. Numerical results demonstrate that the proposed method is promising, especially in comparison with the existing methods."}]