Minimizing the real functions of the ICEC'96 contest by differential evolution
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Differential Evolution (DE) has recently proven to be an efficient method for optimizing real-valued multi-modal objective functions. Besides its good convergence properties and suitability for parallelization, DE's main assets are its conceptual simplicity and ease of use. This paper describes two variants of DE which were used to minimize the real test functions of the ICEC'96 contest.
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