An introduction to differential evolution
New ideas in optimization
How to solve it: modern heuristics
How to solve it: modern heuristics
Journal of Global Optimization
Two improved differential evolution schemes for faster global search
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Differential Evolution with Noise Analyzer
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Recent advances in differential evolution: a survey and experimental analysis
Artificial Intelligence Review
A differential evolution for optimisation in noisy environment
International Journal of Bio-Inspired Computation
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Differential Evolution (DE) is a simple and surprisingly efficient algorithm for global optimization over continuous spaces. It has reportedly outperformed many versions of EA and other search heuristics when tested over both benchmark and real world problems. However the performance of DE deteriorates severely if the fitness function is noisy and continuously changing. In this paper we propose an improved DE scheme which can efficiently track the global optima of a noisy function. The scheme performs better than the classical DE, PSO, and an EA over a set of benchmark noisy problems.