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DE has attracted much attention recently as an effective approach for solving numerical optimization problems. The performance of DE is sensitive to the choice of the mutation and crossover strategies and their associated control parameters. In EPSDE, a pool of distinct mutation and crossover. Strategies and values for each control parameter coexist throughout the evolution process and compete to produce offspring.

Author

Nirjhor Roy

Language

EN