Abstract
This paper presents a component-based model with a novel ranking method (CMR) for constrained evolutionary optimization. In general, many constraint-handling techniques inevitably solve two important problems: (1) how to generate the feasible solutions, (2) how to direct the search to find the optimal feasible solution. For the first problem, this paper introduces a component-based model. The model is useful for exploiting valuable information from infeasible solutions and for transforming infeasible solutions into feasible ones. Furthermore, a new ranking strategy is designed for the second problem. The new algorithm is tested on several well-known benchmark functions, and the empirical results suggest that it continuously found the optimums in 30 runs and has better standard deviations for robustness and stability.
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Wu, Y., Li, Y., Xu, X. (2009). A Novel Component-Based Model and Ranking Strategy in Constrained Evolutionary Optimization. In: Huang, R., Yang, Q., Pei, J., Gama, J., Meng, X., Li, X. (eds) Advanced Data Mining and Applications. ADMA 2009. Lecture Notes in Computer Science(), vol 5678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03348-3_35
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DOI: https://doi.org/10.1007/978-3-642-03348-3_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03347-6
Online ISBN: 978-3-642-03348-3
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