Observations in using Grid-enabled technologies for solving multi-objective optimization problems

In this paper, we analyze some technical issues concerning the use of Grid-enabled technologies based on the Globus Toolkit to solve multi-objective optimization problems. We develop two distributed algorithms: an enumerative search and an evolutionary algorithm. The former is a simple technique, whose high time complexity is mastered down to acceptable execution times to some extent by the use of a Grid-enabled computing system such Globus. The second algorithm is an extension of PAES, a sequential evolutionary algorithm. The parallel results indicate that using Globus is a promising research line to solve multi-objective problems in Grid computing environments.