Korean Journal of Construction Engineering and Management (한국건설관리학회논문집)

Korea Institute of Construction Engineering and Management (한국건설관리학회)
권호 표지

Efficient Elitist Genetic Algorithm for Resource-Constrained Project Scheduling

  • Kim, Jin-Lee (Department of Engineering Technology, Missouri Western State University)
  • Published : 2007.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

This research study presents the development and application of an Elitist Genetic Algorithm (Elitist GA) for solving the resource-constrained project scheduling problem, which is one of the most challenging problems in construction engineering. Main features of the developed algorithm are that the elitist roulette selection operator is developed to preserve the best individual solution for the next generation so as to obtain the improved solution, and that parallel schedule generation scheme is used to generate a feasible solution to the problem. The experimental results on standard problem sets indicate that the proposed algorithm not only produces reasonably good solutions to the problems over the heuristic method and other GA, but also can find the optimal and/or near optimal solutions for the large-sized problems with multiple resources within a reasonable amount of time that will be applicable to the construction industry. This paper will help researchers and/or practitioners in the construction project scheduling software area with alternative means to find the optimal schedules by utilizing the advantages of the Elitist GA.

Keywords

References

  1. Alcaraz, J. and Maroto, C. (2001)'. A Robust Genetic Algorithm for Resource Allocation in Project Scheduling.' Annals of Operations Research, 102, pp. 83-109 https://doi.org/10.1023/A:1010949931021
  2. Bedworth, D. D. and Bailey, J. E. (1982). Integrated Production Control Systems-Management, Analysis, Design, Wiley, New York. N.Y
  3. Blazewicz, J., Lenstra, J. K., and Rinnooy Kan, A. H. G. (1983).' Scheduling Subject to Resource Constraint: Classification and Complexity.' Discrete Applied Mathematics, 5, pp. 11-24 https://doi.org/10.1016/0166-218X(83)90012-4
  4. Brucker, P. and Knust, S. (2003). 'Lower Bounds for Resource-Constrained Project Scheduling Problems.' European Journal of Operations Research, 149, pp. 302-313 https://doi.org/10.1016/S0377-2217(02)00762-2
  5. Brucker, P., Knust, S., Schoo, A., and Thiele, O. (1998). 'A Branch and Bound Algorithm for the Resource-Constrained Project Scheduling Problems.' European Journal of Operations Research, 107(2), pp. 272-288 https://doi.org/10.1016/S0377-2217(97)00335-4
  6. Chan, W., Chua, D. K. H., and Kannan, G. (1996). 'Construction Resource Scheduling with Genetic Algorithms.' Journal of Construction Engineering and Management, ASCE, 122(2), pp. 125-132 https://doi.org/10.1061/(ASCE)0733-9364(1996)122:2(125)
  7. De Jong, K. A. (1975). An Analysis of the Behavior of a Class of Genetic Adaptive Systems, Ph.D. Dissertation, University of Michigan, Ann Arbor, Mich
  8. Demeulemeester, E. L. and Herroelen, W. S. (1997). 'New Benchmark Results for the Resource Constrained Project Scheduling Problem.' Management Science, 43(11), pp. 1485-1492 https://doi.org/10.1287/mnsc.43.11.1485
  9. Goldberg, D. E. (1989). Genetic Algorithms in Search, Optimization, and Machine Learning, Addison- Wesley Publishing Company, Inc., Reading, Massachusetts
  10. Hartmann, S. (1998). 'A Competitive Genetic Algorithm for Resource-Constrained Project Scheduling.' Naval Research Logistics, 45, pp. 733- 750 https://doi.org/10.1002/(SICI)1520-6750(199810)45:7<733::AID-NAV5>3.0.CO;2-C
  11. Hartmann, S. (2002). 'A Self-Adapting Genetic Algorithm for Project Scheduling under Resource Constraints.' Naval Research Logistics, 49, pp. 433- 448 https://doi.org/10.1002/nav.10029
  12. Hegazy, T. (1999). 'Optimization of Resource Allocation and Leveling Using Genetic Algorithms.' Journal of Construction Engineering and Management, ASCE, 125(3), pp. 167-175 https://doi.org/10.1061/(ASCE)0733-9364(1999)125:3(167)
  13. Hegazy, T. and Kassab, M. (2003). 'Resource Optimization Using Combined Simulation and Genetic Algorithms.' Journal of Construction Engineering and Management, ASCE, 129(6), pp. 698-705 https://doi.org/10.1061/(ASCE)0733-9364(2003)129:6(698)
  14. Hindi, K. S., Yang, H., and Fleszar, K. (2002). 'An Evolutionary Algorithm for Resource-Constrained Project Scheduling.' IEEE Transactions on Evolutionary Computation, 6(5), pp. 512-518 https://doi.org/10.1109/TEVC.2002.804914
  15. Holland, J. K. (1975). Adaptation in Neural and Artificial Systems, University of Michigan Press, Ann Arbor, MI
  16. Kelley, J. E. Jr. (1963). 'The Critical-Path Method: Resources Planning and Scheduling.' In J. F. Muth and G. L. Thompson (Eds.), Industrial Scheduling, Prentice-Hall, New Jersey, pp. 347-365
  17. Klein, R. and Scholl, A. (1999). 'Computing Lower Bounds by Destructive Improvement: An Application to Resource-Constrained Project Scheduling.' European Journal of Operational Research, 112, pp. 322-346 https://doi.org/10.1016/S0377-2217(97)00442-6
  18. Kohlmorgen, U., Schmeck, H., and Haase, K. (1999). 'Experiences with Fine-Grained Parallel Genetic Algorithms.' Annals of Operations Research, 90, pp. 203-219 https://doi.org/10.1023/A:1018912715283
  19. Kolisch, R. and Sprecher, A. (1996). 'PSPLIB - A Project Scheduling Problem Library.' European Journal of Operational Research, 96, pp. 205-216
  20. Lee, J.-K. and Kim, Y.-D. (1996).'Search Heuristics for Resource-Constrained Project Scheduling.' The Journal of the Operational Research Society, 47(5), pp. 678-689 https://doi.org/10.2307/3010018
  21. Leu, S. and Yang, C. (1999). 'GA-Based Multicriteria Optimal Model for Construction Scheduling.' Journal of Construction Engineering and Management, ASCE, 125(6), pp. 420-427 https://doi.org/10.1061/(ASCE)0733-9364(1999)125:6(420)
  22. Leu, S., Chen, A., and Yang, C. (1999). 'Fuzzy Optimal Model for Resource-Constrained Construction Scheduling.' Journal of Computing in Civil Engineering, 13(3), pp. 207-216 https://doi.org/10.1061/(ASCE)0887-3801(1999)13:3(207)
  23. Moselhi, O. and Lorterapong, P. (1993). 'Least Impact Algorithm for Resource Allocation.' Canadian Journal of Civil Engineering, CSCE, 20(2), pp. 180-188 https://doi.org/10.1139/l93-023
  24. Shanmuganayagam, V. (1989). 'Current Float Techniques for Resource Scheduling.' Journal of Construction Engineering and Management, ASCE, 115(3), pp. 401-411 https://doi.org/10.1061/(ASCE)0733-9364(1989)115:3(401)
  25. Toklu, Y. C. (2002).' Application of Genetic Algorithms to Construction Scheduling With or Without Resource Constraints.' Canadian Journal of Civil Engineering, 29, pp. 421-429 https://doi.org/10.1139/l02-034
  26. Valls, V., Ballestin, F., and Quintanilla, S. (2005). 'Justification and RCPSP: A Technique That Pays.' European Journal of Operational Research, 165, pp. 375-386 https://doi.org/10.1016/j.ejor.2004.04.008
  27. Zhuang, M. and Yassine, A. A. (2004). 'Task Scheduling of Parallel Development Projects using Genetic Algorithm.' Proceedings of ASME 2004 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Salt Lake City, Utah USA, September 28-October 2, 2004, pp. 1-11