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An improved differential evolution algorithm is given. In the algorithm a logarithm increased crossover and a random migration operator are used to overcome the convergent slowness in the later period of the iteration and fall easily into premature convergence. It is shown by the experiments on eight typical problems that the modified algorithm has strongly global search ability.
Differential evolution (DE) has recently emerged as a leading methodology for global search and optimization over continuous, high-dimensional spaces. It has been successfully applied to a wide variety of nearly intractable engineering problems. However, the DE and its variants usually employ a deterministic selection mechanism that always allows the better solution to survive to the next generation...
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