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Adaptive strategy in differential evolution via explicit exploitation and exploration controls
In the SCSS generations, the exploitation and exploration needs are learnt by utilizing a balanced strategy.
Multi-Layer Competitive-Cooperative Framework for Performance Enhancement of Differential Evolution
Unlike other multi-method strategies which adopt a multi-population based structure, with individuals only evolving in their corresponding subpopulations, MLCC implements a parallel structure with the entire population simultaneously monitored by multiple DEs assigned to their corresponding layers.
Selective-Candidate Framework with Similarity Selection Rule for Evolutionary Optimization
The difficulties lie in obtaining a good balance in EEC, which is determined cooperatively by operations and parameters in an EOA.
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