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Title: A multi-objective genetic algorithm for software development team staffing based on personality types
Authors: Stylianou, Constantinos
Andreou, Andreas S. 
Keywords: Five-Factor Model
IT industry
Multi-objective genetic algorithm
Optimal staffing
Personality traits
Personality types
Real world projects
Software developer
Software development teams
Software project
Software project management
Software quality
Team staffing
Technical skills
Artificial intelligence
Computer software selection and evaluation
Genetic algorithms
Job satisfaction
Project management
Software design
Personnel selection
Issue Date: 2012
Publisher: International Federation for Information Processing
Source: 8th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, Halkidiki, Greece, 27-30 September 2012
Abstract: This paper proposes a multi-objective genetic algorithm for software project team staffing that focuses on optimizing human resource usage based on technical skills and personality traits of software developers. Human factors are recognized as critical aspects affecting the rate of success of software projects, as well as other properties, such as productivity, software quality, performance, and job satisfaction. However, managers often rely solely on technical criteria to staff their projects, which risks overlooking these important aspects of software development, such as the abilities and work styles of developers. The behaviour and scalability of the algorithm was validated against a series of hypothetical projects of varying size and complexity, and also through a real-world project of an SME in the local IT industry. The approach demonstrated a sufficient ability to generate both feasible and optimal staffing solutions by assigning developers most technically competent and suited personality-wise for each project task.
ISSN: 18684238
DOI: 10.1007/978-3-642-33409-2_5
Rights: © 2012 IFIP
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers

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