Computational Intelligence for Information Technology Project Management

Computational Intelligence for Information Technology Project Management

Robert J. Hammell (Towson University, USA), Julie Hoksbergen (Towson University, USA), James Wood (Towson University, USA) and Mark Christensen (Towson University, USA)
DOI: 10.4018/978-1-61520-605-6.ch005
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With the growing complexity of information technology (IT) projects, the management of these projects is proving to be a daunting task. The magnitude of this problem is underscored by the assertion that approximately 70% of IT projects fail to meet their objectives (Lewis, 2007). Computational intelligence (CI) is an area of research focused on developing intelligent systems to help with complex problems. Specifically, CI seeks to integrate techniques and methodologies to assist in problem domains in which information, data and perhaps even the problem itself are vague, approximate, and uncertain. It would seem that research aimed at leveraging the power of CI against IT project management problems is critical if IT project success rates are to be improved. This work examines the core CI technologies – fuzzy logic, neural networks, and genetic algorithms – and looks at current and potential future applications of these techniques to assist IT project managers.
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This section presents the background information related to computational intelligence necessary to understand the discussion regarding current and potential applications of computational intelligence constructs to the project management domain. A discussion of what computational intelligence means is provided first, and then each of its core technologies that are relevant to this work are presented and described. These technologies include fuzzy logic (FL), neural networks (NN), and genetic algorithms (GA). Finally, a summary of the background information is given along with some comments on two other computational intelligence technologies.

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