Introduces a single-number performance measure, file-based benchmarking, and efficient text-file storage to evaluate and compare stopping criteria for EMO algorithms.
Fonseca, and Vi- viane Grunert da Fonseca
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Benchmarking Stopping Criteria for Evolutionary Multi-objective Optimization
Introduces a single-number performance measure, file-based benchmarking, and efficient text-file storage to evaluate and compare stopping criteria for EMO algorithms.