Parallel implementation of evolutionary strategies on heterogeneous clusters with load balancing
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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Abstract: We examine the results of previous attempts to apply genetic and evolutionary computation (GEC) to image processing. In many problems, the accuracy (quality) of solutions obtained by GEC-based methods is better than that obtained by others such as conventional methods, neural networks (NNs) and simulated annealing (SA). However, the computation time required is satisfactory in some problems, whereas it is unsatisfactory in others. We consider the current problems of GEC-based methods and present several measures to achieve still better performance.