Abstract
Population-based methods are often considered superior on multimodal functions because they tend to explore more of the fitness landscape before they converge. We show that the effectiveness of this strategy is highly dependent on a function's global structure. When the local optima are not structured in a predictable way, exploration can misguide search into sub-optimal regions. Limiting exploration can result in a better non-intuitive global search strategy. © 2008 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Lunacek, M., Whitley, D., & Sutton, A. (2008). The impact of global structure on search. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5199 LNCS, pp. 498–507). https://doi.org/10.1007/978-3-540-87700-4_50
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