Generalized descent for global optimization

Abstract:

This paper introduces a new method for the global unconstrained minimization of a differentiable objective function. The method is based on search trajectories, which are defined by a differential equation and exhibit certain similarities to the trajectories of steepest descent. The trajectories depend explicitly on the value of the objective function and aim at attaining a given target level, while rejecting all larger local minima. Convergence to the gloal minimum can be proven for a certain class of functions and appropriate setting of two parameters. © 1981 Plenum Publishing Corporation.

Año de publicación:

1981

Keywords:

• Global optimization
• generalized descent
• target level
• search trajectories

Fuente:

scopus