Examination of Stopping Criteria for Differential Evolution based on a Power Allocation Problem

Abstract

Usually the primary goal for the application
of optimization algorithms is convergence to the global
optimum, and the secondary goal is to use the least
computational effort. By application of different stopping
criteria the achievement of both objectives is influenced: If
an optimization run is terminated too early, convergence
may not be reached, but on the other hand computational
resources may be wasted if the optimization run is stopped
late. Because the two criteria that are applied mostly in
evolutionary algorithms literature have some drawbacks,
several stopping criteria are analyzed in this work, using the
Differential Evolution algorithm. In contrast to a prior study
a constrained optimization problem is used here. It consists
of optimizing the power allocation for a CDMA (Code
Division Multiple Access) system that includes a parallel
interference cancellation technique.