Optimization in a distributed processing environment using genetic algorithms with multivariate crossover

Abstract

We set out to demonstrate the effectiveness of distributed genetic algorithms using multivariate crossover in optimizing a function of a sizable number of independent variables. Our results show that this afgorithm has unique potential in optimizing such functions. The muhivariate crossover mets-strategy, however, did not result in a singularly better performance of the algorithm than did simplier crossover s~ategies.