Volume 2, Issue 2 · IJARST · ISSN 2319-1783 / 2320-1126

Review Of Revolutionary algorithms as an Optimization tool for test cases

Review Of Revolutionary algorithms as an Optimization tool for test cases is an open-access, peer-reviewed research paper by Sujit Kumar panda*, Smruti Ranjan Swain and Aradhana Sahoo, published in Volume 2, Issue 2 of the International Journal of Advanced Research in Science and Technology (IJARST), a UGC-approved journal (Print ISSN 2319-1783, Online ISSN 2320-1126).

Author

Sujit Kumar panda*, Smruti Ranjan Swain and Aradhana Sahoo

Abstract

Abstract:

The aim of this paper is , we focus on one such non-traditional optimization method which takes the ion's share of all non-traditional optimization methods. This so-called 'evolutionary algorithm (EA)' mimics the natural evolutionary principles on randomly-picked solutions from the search space of the problem and iteratively progresses towards the optimum point. Nature's ruthless selective advantage to interest individuals and creation of new and fit individuals using re-combinative and mutative genetic processing with generations is well- mimicked artificially in a computer algorithm to be played on a search space where good and bad solutions to the underlying problem coexist. The task of an evolutionary optimization algorithm is then to avoid the bad solutions in the search space, take clues from good solutions and eventually reach close to the best solution, similar to the genetic processing in natural systems.

DOI

https://doi.org/10.62226/ijarst20130275

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How do you cite this paper?

Sujit Kumar panda*, Smruti Ranjan Swain and Aradhana Sahoo — “Review Of Revolutionary algorithms as an Optimization tool for test cases.” International Journal of Advanced Research in Science and Technology (IJARST), Volume 2, Issue 2. DOI: https://doi.org/10.62226/ijarst20130275.

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