Cooperative co-evolutionary optimization of software project staff assignments and job scheduling

  • Authors:

  • Jian Ren;Mark Harman;Massimiliano Di Penta

  • Affiliations:

  • Department of Computer Science, University College London, UK;Department of Computer Science, University College London, UK;Department of Engineering, University of Sannio, Italy

  • Venue:
  • SSBSE'11 Proceedings of the Third international conference on Search based software engineering
  • Year:
  • 2011

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Abstract

This paper presents an approach to Search Based Software Project Management based on Cooperative Co-evolution. Our approach aims to optimize both developers' team staffing and work package scheduling through cooperative co-evolution to achieve early overall completion time. To evaluate our approach, we conducted an empirical study, using data from four real-world software projects. Results indicate that the Co-evolutionary approach significantly outperforms a single population evolutionary algorithm. Cooperative co-evolution has not previously been applied to any problem in Search Based Software Engineering (SBSE), so this paper reports the first application of cooperative coevolution in the SBSE literature. We believe that co-evolutionary optimization may fit many applications in other SBSE problem domains, since software systems often have complex inter-related subsystems and are typically characterized by problems that need to be co-evolved to improve results.