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A genetic algorithm basic approach for software management project

Published: 22 June 2012 Publication History

Abstract

The scheduling of tasks and project activities is a hard problem and is one of the principal challenges of project management. Most Project Management techniques provide passive project tracking and reporting aids. In this paper Genetic Algorithm technique is used to search for near-optimum solution -- shorter project duration and minimum project cost. The proposed model is called IGAPM (Implementation Genetic Algorithm for Project Management). The major advantages of IGAPM algorithm is its simple applicability within software management project and the improvement of initial population, accelerates the GA process.

References

[1]
Alba E., Chicano J. F., Software project management with Gas, Information Sciences 177, An Iternational Journal, pp.2380--2401, 2007.
[2]
Braune R., Wagner S., Applying Genetic Algorithm for the Optimization of the production planning in real World manufacturing environment, 2008
[3]
Chao C., "SPMNET: A new Methodology for Software Management", PhD Thesis, The University of Illinois at Chicago, 1995
[4]
Ramzan M., Quazim K., Amjad M, A genetic algorithms based for conflicts resolution in requirements, International Journal of the Physical Sciences Vol. 6, pp.828--836, 2011
[5]
http://www.pmipr.org/html/Presentaciones/The Critical Path Method.pdf
[6]
http://www.codeproject.com/KB/recipes/CriticalPathMethod.aspx.

Cited By

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  • (2023)Creative AI in Software Project Management2023 2nd International Conference on Futuristic Technologies (INCOFT)10.1109/INCOFT60753.2023.10425234(1-9)Online publication date: 24-Nov-2023
  • (2019)Application of Genetic Algorithms for Decision-Making in Project Management: A Literature ReviewInformation Technology and Management Science10.7250/itms-2019-000422(22-31)Online publication date: 23-Dec-2019
  1. A genetic algorithm basic approach for software management project

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    cover image ACM Other conferences
    CompSysTech '12: Proceedings of the 13th International Conference on Computer Systems and Technologies
    June 2012
    440 pages
    ISBN:9781450311939
    DOI:10.1145/2383276
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 22 June 2012

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    Author Tags

    1. constraints
    2. crossover
    3. genetic algorithms
    4. mutation
    5. planning
    6. selection
    7. software project management

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    Cited By

    View all
    • (2023)Creative AI in Software Project Management2023 2nd International Conference on Futuristic Technologies (INCOFT)10.1109/INCOFT60753.2023.10425234(1-9)Online publication date: 24-Nov-2023
    • (2019)Application of Genetic Algorithms for Decision-Making in Project Management: A Literature ReviewInformation Technology and Management Science10.7250/itms-2019-000422(22-31)Online publication date: 23-Dec-2019

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