In this paper, we propose a new hybrid coefficient of conjugate gradient method (CG) for solving unconstrained optimization model. The is combination part the MMSIS (Malik et.al, 2020) and PRP (Polak, Ribi'ere \& Polyak, 1969) coefficients. Under exact line search, search direction satisfies sufficient descent condition based on certain assumption, establish global convergence properties. U...

In this paper, we propose a new descent method, called multiobjective memory gradient for finding Pareto critical points of optimization problem. The main thought in method is to select combination the current direction and past multi-step iterative information as search obtain stepsize by two types strategies. It proved that developed with suitable parameters always satisfies sufficient condit...

In this paper, we derive a new parameter µk-1 for the three-term CG (N3T) algorithm solving unconstrained optimization problems. As demonstrated by its calculations and proof, worth is determined T , study mentions four different types of . The search directions are always sufficiently descent when using strong Wolfe line (SWC). Under reasonable assumptions, proposed achieves global convergence...

A characterization of descent morphism in the category of Priestley spaces, as well as necessary and sufficient conditions for such morphisms to be effective are given. For that we embed this category in suitable categories of preordered topological spaces were descent and effective morphisms are described using the monadic description of descent.

A modification of the Dai-Yuan conjugate gradient algorithm is proposed. Using the exact line search, the algorithm reduces to the original version of the Dai and Yuan computational scheme. For inexact line search the algorithm satisfies both the sufficient descent and conjugacy condition. A global convergence result is proved when the Wolfe line search conditions are used. Computational result...

The rotation averaging problem is a fundamental task in computer vision applications. It generally very difficult to solve due the nonconvex constraints. While sufficient optimality condition available literature, there lack of fast convergent algorithm achieve stationary points. In this paper, by exploring structure, we first propose block coordinate descent (BCD)-based with guaranteed converg...