• DocumentCode
    2590615
  • Title

    Project Scheduling Conflict Identification and Resolution Using Genetic Algorithms

  • Author

    Ramzan, M. ; Iqbal, M. Amjad ; Jaffar, M. Arfan ; Rauf, Abdul ; Anwar, Sajid ; Shahid, Arshad ali

  • Author_Institution
    Nat. Univ. of Comput. & Emerging Sci. (FAST-NU), Islamabad, Pakistan
  • fYear
    2010
  • fDate
    21-23 April 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Project management is one very critical task of development activity. Project management is traditionally defined as the discipline of planning, organizing, and managing activities and resources for successful execution and completion of project goals and objectives. In this respect, project management holds a key position in satisfactory completion of projects. Project management for software holds the same importance in software development. That is the reason that we have a complete knowledge domain we know as software project management (SPM). Software project management aims to achieve all the project goals and objectives while working within the constraints posed by project environment and stakeholders. These constraints include (but not limited to) time, scope, resources, resource allocation and optimization etc. While managing software projects, it is natural to be confronted with various conflicts of different natures. A good project management activity is one which can effectively foresee these conflicts and resolve them in an optimal fashion. In this paper, a genetic algorithm based technique for conflict identification and resolution for project activities has been proposed. The effectiveness and utility of such a technique has also been discussed in this paper.
  • Keywords
    genetic algorithms; project management; scheduling; software engineering; software management; genetic algorithms; project scheduling conflict identification; project scheduling conflict resolution; resource allocation; software development; software project management; Character recognition; Computer networks; Genetic algorithms; Handwriting recognition; Inference algorithms; Network topology; Neural networks; Optimization methods; Recurrent neural networks; Wind speed;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Applications (ICISA), 2010 International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4244-5941-4
  • Electronic_ISBN
    978-1-4244-5943-8
  • Type

    conf

  • DOI
    10.1109/ICISA.2010.5480400
  • Filename
    5480400