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Incorporating Ancestors' Influence in Genetic Algorithms

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Abstract

A new criterion of fitness evaluation for Genetic Algorithms is introduced where the fitness value of an individual is determined by considering its own fitness as well as those of its ancestors. Some guidelines for selecting the weighting coefficients for quantifying the importance to be given to the fitness of the individual and its ancestors are provided. This is done both heuristically and automatically under fixed and adaptive frameworks. The Schema Theorem corresponding to the proposed concept is derived. The effectiveness of this new methodology is demonstrated extensively on the problems of optimizing complex functions including a noisy one and selecting optimal neural network parameters.

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Authors and Affiliations

  1. Department of Computer Science & Engineering, Jadavpur University, Kolkata, 700 032, India

    Susmita Ghosh

  2. Machine Intelligence Unit, Indian Statistical Institute, 203 B.T. Road, Kolkata, 700 108, India

    Ashish Ghosh & Sankar K. Pal

Authors
  1. Susmita Ghosh
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  2. Ashish Ghosh
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  3. Sankar K. Pal
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Ghosh, S., Ghosh, A. & Pal, S.K. Incorporating Ancestors' Influence in Genetic Algorithms. Applied Intelligence 18, 7–25 (2003). https://doi.org/10.1023/A:1020955300403

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