Journal of Global Optimization
Population set-based global optimization algorithms: some modifications and numerical studies
Computers and Operations Research
Influence of crossover on the behavior of Differential Evolution Algorithms
Applied Soft Computing
Differential evolution algorithm with strategy adaptation for global numerical optimization
IEEE Transactions on Evolutionary Computation
Recent advances in differential evolution: a survey and experimental analysis
Artificial Intelligence Review
JADE: adaptive differential evolution with optional external archive
IEEE Transactions on Evolutionary Computation
Differential evolution algorithm with ensemble of parameters and mutation strategies
Applied Soft Computing
IEEE Transactions on Evolutionary Computation
Differential Evolution: A Survey of the State-of-the-Art
IEEE Transactions on Evolutionary Computation
Differential Evolution With Composite Trial Vector Generation Strategies and Control Parameters
IEEE Transactions on Evolutionary Computation
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Two adaptive approaches applied in competitive differential evolution and in differential evolution with an ensemble of mutation strategies and parameter values are compared. The approach used in each of these two algorithms can be divided into two parts: adaptive mechanism and pool of strategies. Four variants of adaptation in differential evolution mutually combining these two parts of the two algorithms are experimentally compared in six benchmark functions at two levels of dimension. It was found out that the algorithms with the pool of competitive differential evolution are more reliable, whereas the variants using the pool of the other algorithm need mostly a smaller number of function evaluations to reach the stopping condition.