THE ANNEALING EVOLUTION ALGORITHM AS FUNCTION OPTIMIZER

In this paper an annealing evolution algorithm is applied to the optim ization of continuous problems. The algorithm uses an evolutionary str ategy to guide the search in simulated annealing. Furthermore, we disc uss an implementation of the algorithm and compare its performance wit h the conventional simulated annealing algorithm and the parallel gene tic algorithm. The performance evaluation is carried out for a standar d set of test functions from the literature. Here a breakthrough can b e reported. The annealing evolution algorithm is able to find the glob al minimum of Rastrigin's function of dimension 500 on the VAX 8600 ma chine.