Parallelizing Mutations for Genetic Algorithm

Authors

  • Ankush Rai Department of Applied Science, CRIAD Laboratories, Smiriti Nagar-490020, India

DOI:

https://doi.org/10.37591/rtpc.v1i3.245

Abstract

In the present work, the author has implemented the mutations crossovers of genetic algorithm (GA) over a parallelism environment. This attempt will enable us collect data to build a framework for shared parallelism for the solution of equations in the same verifiable computational time. The data indicate towards the better implementation of a larger computational problem in the parallelized for the better solution in the verifiable execution time.

Keywords: Genetic algorithm, parallelism, time complexity

 

Author Biography

  • Ankush Rai, Department of Applied Science, CRIAD Laboratories, Smiriti Nagar-490020, India

    Hi, I am Ankush Rai currently involved into extensive Research in Interdisciplinary fields to
    integrate Computer Science, Neurobiology & Computational Anthropology into one fabric of
    "Autonomous Data Processors". Additionally I've 3 years of consultancy experience in
    software development. Assessing throughput of technological problems and building
    comprehensive solution with applicability is my driving force.

    Educational Qualification:
    PhD : Computer Science
    University- CSVTU
    Thesis Title : Mathematical Proof of P=NP : A Major Step in Theoretical Computer Science
    Characteristics: Heuristic, Pragmatic & Polymath
    Area of Expertise: Artificial Intelligence, Mathematical Modelling, Computation & Data
    Modelling, Computer Simulation, Computer Network &
    Multidisciplinary approach for research design and conduct.
    Postdoctoral Fellow: MIT (Massachusetts Institute of Technology, Boston, USA) for 2
    years.

    Hobbies: Graphite Sketching, writing-poetry, playing piano, contemplating & admiring talents of others.

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Published

2015-01-01

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Section

Case Study