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Project scheduling conflict identification and resolution using genetic algorithms (GA)

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Abstract

Project management has gained a lot of application in software development activity in the past two decades. It is now considered to be one of the most critical component of software development lifecycle. 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. That is the reason that we have a complete knowledge domain we know as software project management (SPM). The main purpose of SPM is 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. Successful project planning involved careful selection and synchronization of resources in order to achieve satisfactory completion of projects. These resources include human resource, rime, infrastructure etc. While planning software projects, it is natural to be confronted with various conflicts in resource allocation. It becomes a very time consuming activity to identify and sort out these conflicts when project size is large and time constraints are severe. A good project management activity is one which can effectively foresee these conflicts and resolve them in an optimal fashion. Computationally intelligent techniques are a good candidate to be used for the purpose of automation of this task. 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. The technique has been subjected to extensive experimentation and results have been presented.

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Authors and Affiliations

  1. National University of Computer and Emerging Sciences (FAST-NU), A.K. Brohi Road, H11/4, Islamabad, Pakistan

    Muhammad Ramzan, Arfan Jaffar, Amjad Iqbal, Sajid Anwar, Abdul Rauf & Arshad Ali Shahid

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  1. Muhammad Ramzan
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  2. Arfan Jaffar
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  3. Amjad Iqbal
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  4. Sajid Anwar
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  5. Abdul Rauf
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  6. Arshad Ali Shahid
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Correspondence to Arfan Jaffar.

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Ramzan, M., Jaffar, A., Iqbal, A. et al. Project scheduling conflict identification and resolution using genetic algorithms (GA). Telecommun Syst 51, 167–175 (2012). https://doi.org/10.1007/s11235-011-9426-3

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