Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Multiobjective evolutionary algorithm test suites
Proceedings of the 1999 ACM symposium on Applied computing
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
An Investigation of Niche and Species Formation in Genetic Function Optimization
Proceedings of the 3rd International Conference on Genetic Algorithms
MOPSO: a proposal for multiple objective particle swarm optimization
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Muiltiobjective optimization using nondominated sorting in genetic algorithms
Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
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In previous work, a neural network was used to increase the number of solutions found by an evolutionary multiobjective optimization algorithm. In this paper, various approaches are applied in the training of the neural network to determine whether an approach exists that can provide reasonable results in a reasonable time. To this end, two heuristic training algorithms are developed. When evaluated on a suite of ten benchmark mutliobjective optimization problems, these heuristic techniques perform very well and, on average, produce many more solutions than the evolutionary multiobjective optimization approach alone.