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Comprehensive Parent Selection-based Genetic Algorithm

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Research and Development in Intelligent Systems XXIX (SGAI 2012)

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Abstract

During the past few years, many variations of genetic algorithm (GA) have been proposed. These algorithms have been successfully used to solve problems in different disciplines such as engineering, business, science, and networking etc. Real world optimization problems are divided into two categories: (1) single objective, and (2) multi-objective. Genetic algorithms have key advantages over other optimization techniques to deal with multi-objective optimization problems. One of the most popular techniques of GA to obtain the Pareto-optimal set of solutions for multi-objective problems is the non-dominated sorting genetic algorithm- II (NSGA-II). In this paper, we propose a variant of NSGA-II that we call the comprehensive parent selection-based genetic algorithm (CPSGA). The proposed strategy uses the information of all the individuals to generate new offspring from the selected parents. This strategy ensures diversity to discourage premature convergence. CPSGA is tested using the standard ZDT benchmark problems and the performance metrics taken from the literature. Moreover, the results produced are compared with the original NSGA-II algorithm. The results show that the proposed approach is a viable alternative to solve multi-objective optimization problems.

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Author information

Authors and Affiliations

  1. Department of Computer Science, National University of Computer and Emerging Sciences, A. K. Brohi Road H-11/4, Islamabad, Pakistan

    Hamid Ali

  2. Center of Excellence in Information Assurance, King Saud University Riyadh, Riyadh, Saudi Arabia

    Farrukh Aslam Khan

Authors
  1. Hamid Ali
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  2. Farrukh Aslam Khan
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Corresponding author

Correspondence to Hamid Ali .

Editor information

Editors and Affiliations

  1. School of Computing, University of Portsmouth, Whitepost Lane The Lilacs, Portsmouth, PO1 3AH, Hampshire, United Kingdom

    Max Bramer

  2. School of Computing, Engineering & Mathe, University of Brighton, Lewes Road, Brighton, BN2 4GJ, West Sussex, United Kingdom

    Miltos Petridis

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© 2012 Springer-Verlag London

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Ali, H., Khan, F.A. (2012). Comprehensive Parent Selection-based Genetic Algorithm. In: Bramer, M., Petridis, M. (eds) Research and Development in Intelligent Systems XXIX. SGAI 2012. Springer, London. https://doi.org/10.1007/978-1-4471-4739-8_9

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  • DOI: https://doi.org/10.1007/978-1-4471-4739-8_9

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-4738-1

  • Online ISBN: 978-1-4471-4739-8

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