Evolutionary Computation · 2006 · 258 citations · 3 references
ComputingComputer ScienceMathematicsAlgorithmsArtificial IntelligenceOptimizationEvolutionary ComputationEvolutionary OptimizationEvolutionary AlgorithmsLocal Optimization
The Rosenbrock function is a well-known benchmark for numerical optimization problems, which is frequently used to assess the performance of Evolutionary Algorithms. The classical Rosenbrock function, which is a two-dimensional unimodal function, has been extended to higher dimensions in recent years. Many researchers take the high-dimensional Rosenbrock function as a unimodal function by instinct. In 2001 and 2002, Hansen and Deb found that the Rosenbrock function is not a unimodal function for higher dimensions although no theoretical analysis was provided. This paper shows that the n-dimensional (n = 4 ∼ 30) Rosenbrock function has 2 minima, and analysis is proposed to verify this. The local minima in some cases are presented. In addition, this paper demonstrates that one of the “local minima” for the 20-variable Rosenbrock function found by Deb might not in fact be a local minimum.
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Evolutionary programming made faster
Xin Yao, Yong Liu, Guangming Lin · IEEE Transactions on Evolutionary Computation · 1999 · 3.9K citations