The paper based on B. Martos’ ideas (B. Martos, Nonlinear programming theory and methods, Akademiai Kiado, Budapest 1975. Polish translation PWN 1983) presents theoretical results concerning quasiconvex and pseudoconvex functions.
In this article the theory of local convergence is developed. One of the extensions consists in that the approximations to the Jacobian matrix have the same properties as the same matrix has in the solution. The example shows that this assumption may lead to simpler algorithms. The paper discusses several rescaled multilevel least-change updates for which local g-superlinear convergence is proved. The theory may be applied to a wider class of methods because every secant algorithm may be treated as a rescaled least-change method.
The problem of minimizing a concave function on a convex polyhedron is considered. The author proposes a solution algorithm which, starting from a vertex representing a local minimum of the objective function, constructs a sequence of auxiliary linear programming problems in order to find a global minimum. The convergence of the algorithm is proven.
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In this study, we introduce a new class of function called geodesic semi E-b-vex functions and generalized geodesic semi E-b-vex functions and discuss some of their properties.
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