Survey of Methods to Prevent Premature Convergence in Evolutionary Algorithms
نویسنده
چکیده
Evolutionary algorithms (EA) are general metaheuristic algorithms which have very good characteristics. They are relatively robust and usually generate very good solutions to hard problems [15], [16], [23], [29]. However, they also have many problems with the population converging to a suboptimal solution instead of an optimal one [27], [28]. This occurrence is called premature convergence, and it is of great importance to develop EAs that consistently avoid it.
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