A First-Order Variable Metric Method Invariant to Strictly Increasing Function Value Transformations

Abstract

Incorporating multiple elements of evolution strategies, a first-order variable metric method for unconstrained optimization that is invariant to strictly increasing function value transformations is proposed. The algorithm’s performance is evaluated relative to that of a quasi-Newton algorithm using a large set of test problems.