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Effects of Initial Search Bound on the Performance of Self-adaptive Evolutionary Computation Methods

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 54))

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Abstract

Self-adaptive evolutionary computation methods are widely used for finding global optimum in varieties of problem domains. One of the major demerits of these methods is premature convergence that stuck the search process at one of the local minimum. This paper examines this issue through an exhaustive study on the possible effects of initial search bound on the overall performance of the evolutionary computation methods.

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Swain, A.K. (2010). Effects of Initial Search Bound on the Performance of Self-adaptive Evolutionary Computation Methods. In: Prasad, S.K., Vin, H.M., Sahni, S., Jaiswal, M.P., Thipakorn, B. (eds) Information Systems, Technology and Management. ICISTM 2010. Communications in Computer and Information Science, vol 54. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12035-0_31

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  • DOI: https://doi.org/10.1007/978-3-642-12035-0_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12034-3

  • Online ISBN: 978-3-642-12035-0

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