A multi-objective genetic algorithm for software development team staffing based on personality types - Stylianou, Constantinos; Andreou, Andreas S. (My University, 2012)
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.
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