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This paper introduces a new technique called species conservation for evolving parallel subpopulations. The technique is based on the concept of dividing the population into several species according to their similarity. Each of these species is built around a dominating individual called the species seed. Species seeds found in the current generation are saved (conserved) by moving them into the next generation. Our technique has proved to be very effective in finding multiple solutions of multimodal optimization problems. We demonstrate this by applying it to a set of test problems, including some problems known to be deceptive to genetic algorithms. [ABSTRACT FROM AUTHOR]

Presents an erratum of the article 'A Species Conserving Genetic Algorithm for Multimodal Function Optimization,' by Li et al., published in the 2002 issue of the journal 'Evolutionary Computation.'