An introduction to differential evolution
New ideas in optimization
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
Proceedings of the 8th annual conference on Genetic and evolutionary computation
DEMO: differential evolution for multiobjective optimization
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Environmental Modelling & Software
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We introduce a new synergistic combination of features, some of which have previously been used individually but not together, to improve uniformity of spacing in evolved non-dominated sets, especially in biobjective problems. On five standard biobjective benchmark tests, these features are shown to enhance performance in distinct and complementary ways.