Is Parameters Quantification in Genetic Algorithm Important, How to do it?

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Abstract

The term “appropriate parameters” signifies the correct choice of values has considerable effect on the performance that directs the search process towards the global optima. The performance typically is measured considering both quality of the results obtained and time requires in finding them. A genetic algorithm is a search and optimization technique, whose performance largely depends on various factors – if not tuned appropriately, difficult to get global optima. This paper describes the applicability of orthogonal array and Taguchi approach in tuning the genetic algorithm parameters. The domain of inquiry is grammatical inference has a wide range of applications. The optimal conditions were obtained corresponding to performance and the quality of results with reduced cost and variability. The primary objective of conducting this study is to identify the appropriate parameter setting by which overall performance and quality of results can be enhanced. In addition, a systematic discussion presented will be helpful for researchers in conducting parameters quantification for other algorithms
Original languageEnglish
Pages (from-to)112-123
JournalIAES International Journal of Artificial Intelligence (IJ-AI)
Volume6
Issue number3
Early online date30 Sep 2017
DOIs
Publication statusE-pub ahead of print - 30 Sep 2017

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Genetic algorithms
Tuning
Costs

Keywords

  • Context free grammar
  • Evolutionary computation
  • Genetic algorithm Grammar induction
  • Taguchi design.

Cite this

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title = "Is Parameters Quantification in Genetic Algorithm Important, How to do it?",
abstract = "The term “appropriate parameters” signifies the correct choice of values has considerable effect on the performance that directs the search process towards the global optima. The performance typically is measured considering both quality of the results obtained and time requires in finding them. A genetic algorithm is a search and optimization technique, whose performance largely depends on various factors – if not tuned appropriately, difficult to get global optima. This paper describes the applicability of orthogonal array and Taguchi approach in tuning the genetic algorithm parameters. The domain of inquiry is grammatical inference has a wide range of applications. The optimal conditions were obtained corresponding to performance and the quality of results with reduced cost and variability. The primary objective of conducting this study is to identify the appropriate parameter setting by which overall performance and quality of results can be enhanced. In addition, a systematic discussion presented will be helpful for researchers in conducting parameters quantification for other algorithms",
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Is Parameters Quantification in Genetic Algorithm Important, How to do it? / Pandey, Hari.

In: IAES International Journal of Artificial Intelligence (IJ-AI), Vol. 6, No. 3, 30.09.2017, p. 112-123.

Research output: Contribution to journalArticle

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