Parameters quantification of genetic algorithm

Research output: Chapter in Book/Report/Conference proceedingConference proceeding (ISBN)

1 Citation (Scopus)

Abstract

This paper presents the importance of parameters tuning in global optimization algorithms. The primary objective of an experiment is to recognize the process. The experiments are carried out to learn the effect of various factors at different levels. Hence, identifying the optimal parameters setting is important for robust design. One of the most popular global optimization algorithms: genetic algorithm is considered in this study. The domain of inquiry is travelling salesman problem. The present study employs the Taguchi method that involves the use of an orthogonal array in the estimation of the factors. Taguchi approach has been widely applied in experimental design for problems with multiple factors. The use of Taguchi design is a novel idea—leads to efficient algorithms—can find a satisfactory solution in a few iterations, which improves the convergence speed and reduces the cost. Experimental results show that the Taguchi design is less sensitive to initial value of parameters. Two versions of genetic algorithms (with tuning and without tuning) are implemented. The analysis shows the superiority of genetic algorithm with tuning over genetic algorithm without tuning.

Original languageEnglish
Title of host publicationINFORMATION SYSTEMS DESIGN AND INTELLIGENT APPLICATIONS, VOL 2, INDIA 2016
EditorsSuresh Chandra Satapathy, Jyotsna Kumar Mandal, Siba K. Udgata, Vikrant Bhateja
PublisherSpringer-Verlag
Pages711-719
Number of pages9
Volume434
ISBN (Print)9788132227502
DOIs
Publication statusPublished - 3 Feb 2016
Event3rd International Conference on Information Systems Design and Intelligent Applications, INDIA 2016 - Visakhapatnam, India
Duration: 8 Jan 20169 Jan 2016

Publication series

NameAdvances in Intelligent Systems and Computing
Volume434
ISSN (Print)2194-5357

Conference

Conference3rd International Conference on Information Systems Design and Intelligent Applications, INDIA 2016
CountryIndia
CityVisakhapatnam
Period8/01/169/01/16

Fingerprint

Tuning
Genetic algorithms
Global optimization
Taguchi methods
Traveling salesman problem
Design of experiments
Experiments
Costs

Keywords

  • Aguchi method
  • Genetic algorithm
  • Robust design
  • Travelling salesman problem
  • Taguchi method

Cite this

Pandey, H. M. (2016). Parameters quantification of genetic algorithm. In S. C. Satapathy, J. K. Mandal, S. K. Udgata, & V. Bhateja (Eds.), INFORMATION SYSTEMS DESIGN AND INTELLIGENT APPLICATIONS, VOL 2, INDIA 2016 (Vol. 434, pp. 711-719). (Advances in Intelligent Systems and Computing; Vol. 434). Springer-Verlag. https://doi.org/10.1007/978-81-322-2752-6_70
Pandey, Hari Mohan. / Parameters quantification of genetic algorithm. INFORMATION SYSTEMS DESIGN AND INTELLIGENT APPLICATIONS, VOL 2, INDIA 2016. editor / Suresh Chandra Satapathy ; Jyotsna Kumar Mandal ; Siba K. Udgata ; Vikrant Bhateja. Vol. 434 Springer-Verlag, 2016. pp. 711-719 (Advances in Intelligent Systems and Computing).
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Pandey, HM 2016, Parameters quantification of genetic algorithm. in SC Satapathy, JK Mandal, SK Udgata & V Bhateja (eds), INFORMATION SYSTEMS DESIGN AND INTELLIGENT APPLICATIONS, VOL 2, INDIA 2016. vol. 434, Advances in Intelligent Systems and Computing, vol. 434, Springer-Verlag, pp. 711-719, 3rd International Conference on Information Systems Design and Intelligent Applications, INDIA 2016, Visakhapatnam, India, 8/01/16. https://doi.org/10.1007/978-81-322-2752-6_70

Parameters quantification of genetic algorithm. / Pandey, Hari Mohan.

INFORMATION SYSTEMS DESIGN AND INTELLIGENT APPLICATIONS, VOL 2, INDIA 2016. ed. / Suresh Chandra Satapathy; Jyotsna Kumar Mandal; Siba K. Udgata; Vikrant Bhateja. Vol. 434 Springer-Verlag, 2016. p. 711-719 (Advances in Intelligent Systems and Computing; Vol. 434).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding (ISBN)

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Pandey HM. Parameters quantification of genetic algorithm. In Satapathy SC, Mandal JK, Udgata SK, Bhateja V, editors, INFORMATION SYSTEMS DESIGN AND INTELLIGENT APPLICATIONS, VOL 2, INDIA 2016. Vol. 434. Springer-Verlag. 2016. p. 711-719. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-81-322-2752-6_70