Project Scheduling Problem for Software Development with Random Fuzzy Activity Duration Times

  • Wei Huang
  • Lixin Ding
  • Bin Wen
  • Buqing Cao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5552)


This paper presents a new method that describes activity duration times, which can be as random fuzzy variables to solve the software project scheduling problem. It solves the problem of the present classic models, such as PERT and CPM, which are weak in solving project scheduling problem for software development due to the concurrent, iterative and evolutionary nature characteristics of software projects. Next, a novel stochastic software project scheduling model —expected cost model —is suggested. Furthermore, basing on genetic algorithm and random fuzzy simulation, a hybrid intelligent algorithm is designed to solve the expected cost model. Numerical experiments illustrate the effectiveness of the hybrid intelligent algorithm.


Project scheduling problem for software development Random fuzzy simulation Genetic algorithm Hybrid intelligent algorithm 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Chang, C.K., Christensen, M.: A Net Practice for Software Project Management. IEEE Software 16, 80–89 (1999)CrossRefGoogle Scholar
  2. 2.
    Kelley Jr., J.E.: Critical Path Planning and Scheduling, Mathematical Basis. Operations Research 9, 296–320 (1961)MathSciNetCrossRefzbMATHGoogle Scholar
  3. 3.
    Kelley Jr., J.E.: The Critical Path Method: Resources Planning and Scheduling. In: Thompson, G.L., Muth, J.F. (eds.) Industrial Scheduling. Prentice-Hall, Englewood Cliffs (1963)Google Scholar
  4. 4.
    Burgess, A.R., Killebrew, J.B.: Variation in Activity Level on a Cyclical Arrow Diagram. Journal of Industrial Engineering 13, 76–83 (1962)Google Scholar
  5. 5.
    Demeulemeester, E.: Minimizing Resource Availability Costs in Time-limited Project Networks. Management Science 41, 1590–1598 (1995)CrossRefzbMATHGoogle Scholar
  6. 6.
    Mohring, R.H.: Minimizing Costs of Resource Requirements in Project Networks Subject to a Fixed Completion time. Operations Research 32, 89–120 (1984)CrossRefzbMATHGoogle Scholar
  7. 7.
    Lu, M., Lam, H.C., Dai, F.: Resource-constrained Critical Path Analysis based on discrete event Simulation and Particle Swarm Optimization. Automation in Construction 17, 670–681 (2008)CrossRefGoogle Scholar
  8. 8.
    Liu, S.S., Wang, C.J.: Resource-constrained Construction Project Scheduling Model for Profit Maximization Considering Cash Flow. Automation in Construction 17, 966–974 (2008)CrossRefGoogle Scholar
  9. 9.
    Liu, L.C., Horowitz, E.: A Formal Model for Software Project Management. IEEE Trans.Software Eng. 15, 1280–1293 (1989)CrossRefGoogle Scholar
  10. 10.
    Blum, B.I.: Software Engineering. A Hollstic View. Oxford UnivePress, New York (1992)Google Scholar
  11. 11.
    Chang, C.K., Jiang, H., Di, Y., Zhu, D., Ge, Y.: Time-line Based Model for Software Project Scheduling with Genetic Algorithms. Information and Software Technology 11, 1142–1154 (2008)CrossRefGoogle Scholar
  12. 12.
    Padberg: Scheduling Software Projects to Minimize the Development Time and Cost with a Given Staff. In: Proceedings APSEC, vol. 8, pp. 187–194 (2001)Google Scholar
  13. 13.
    Maciej, Hapke, A.J., Roman, S.: Fuzzy Project Scheduling System for Software Development. Fuzzy Sets and Systems 67, 101–117 (1994)MathSciNetCrossRefzbMATHGoogle Scholar
  14. 14.
    Sana, U.Z.: A Decision Support System for Fuzzy Scheduling of Soft-ware Projects. In: Autotestcon Proceedings, pp. 263–272 (2000)Google Scholar
  15. 15.
    Liu, B., Liu, Y.K.: Expected Value of Fuzzy Variable and Fuzzy Expected Value Models. IEEE Transactions on Fuzzy Systems 10, 445–450 (2002)CrossRefGoogle Scholar
  16. 16.
    Liu, B.: Theory and Practice of Uncertain Programming. Physica-Verlag, Heidelberg (2002)CrossRefzbMATHGoogle Scholar
  17. 17.
    Liu, Y., Liu, B.: Expected Value Operator of Random Fuzzy Variable and Random Fuzzy Expected Value Models. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 11, 195–215 (2003)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Wei Huang
    • 1
    • 2
  • Lixin Ding
    • 1
  • Bin Wen
    • 1
  • Buqing Cao
    • 1
  1. 1.State Key Lab of Software EngineeringWuHan UniversityWuHanChina
  2. 2.JiangXi Agricultural UniversityNanChangChina

Personalised recommendations