The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
Multiobjective evolutionary algorithm test suites
Proceedings of the 1999 ACM symposium on Applied computing
Multicriterion Optimisation in Engineering
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Parallel Computing in Optimization
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Evolutionary Algorithms for Solving Multi-Objective Problems
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PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
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GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
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IEEE Transactions on Evolutionary Computation
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IEEE Transactions on Evolutionary Computation
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IEEE Transactions on Evolutionary Computation
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Proceedings of the 9th annual conference on Genetic and evolutionary computation
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Genetic Programming and Evolvable Machines
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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.