Journal of the Architectural Institute of Korea Structure & Construction (대한건축학회논문집:구조계)

Architectural Institute of Korea (대한건축학회)
권호 표지
DOI QR코드

DOI QR Code

Resource Leveling using Genetic Algorithm

유전알고리즘을 활용한 자원평준화 방법론

  • 곽한성 (경북대학교 건설환경에너지공학부) ;
  • 배상희 (경북대학교 건설환경에너지공학부) ;
  • 이동은 (경북대학교 건설환경에너지공학부)
  • Received : 2017.10.10
  • Accepted : 2017.12.08
  • Published : 2018.02.28
⟨ Previous Next ⟩

Abstract

Resource leveling minimizes resource fluctuations by deferring the earliest start times (ESTs) of non-critical activities within their corresponding total float. The intentional float-consumption for resource leveling purpose reduces the schedule delay contingency. This paper presents a method called Genetic Algorithm based Resource Leveling (GARL) that minimizes resource fluctuations and float-consumption impact over project duration. It identifies activities that are less sensitive to float-consumption and performs resource leveling using those activities. The study is of value to project scheduler because GARL identifies the set of activities to be deferred and the number of shift day(s) of each and every activities in the set within its total float expeditiously. It contributes to establish a baseline schedule which implements an optimal resource leveling plan. A case study is presented to verify the validity and usability of the method. It was confirmed that GARL satisfies the project duration constraint by considering resource fluctuations and float-consumption over project duration.

Keywords

Acknowledgement

Supported by : 한국연구재단

References

  1. Burguess, A. & Killebrew, J. (1962). Variation in activity level on a cyclic arrow diagram. Journal of Industrial Engineering, 13(2), 76-83.
  2. Easa, S. M. (1989). Resource leveling in construction by optimization. Journal of construction engineering and management, 115(2), 302-316. https://doi.org/10.1061/(ASCE)0733-9364(1989)115:2(302)
  3. Elbeltagi, E. Hegazy, T. & Grierson, D. (2005). Comparison among five evolutionary-based optimization algorithms. Advanced engineering informatics, 19(1), 43-53. https://doi.org/10.1016/j.aei.2005.01.004
  4. El-Rayes, K. & Jun, D. H. (2009). Optimizing resource leveling in construction projects. Journal of Construction Engineering and Management, 135(11), 1172-1180. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000097
  5. Damci, A. & Polat, G. (2014). Impacts of different objective functions on resource leveling in construction projects: a case study. Journal of Civil Engineering and Management, 20(4), 537-547. https://doi.org/10.3846/13923730.2013.801909
  6. Harris, R. (1978). Precedence and Arrow Networking Techniques for Construction. Wiley, New York.
  7. Hegazy, T. (1999). Optimization of resource allocation and leveling using genetic algorithms. Journal of construction engineering and management, 125(3), 167-175. https://doi.org/10.1061/(ASCE)0733-9364(1999)125:3(167)
  8. Hendrickson, C. & Au, T. (1989). Project management for construction, Prentice Hall, Pittsburgh, PA.
  9. Hiyassat, M. A. S. (2000). Modification of minimum moment approach in resource leveling. Journal of Construction Engineering and Management, 126(4), 278-284. https://doi.org/10.1061/(ASCE)0733-9364(2000)126:4(278)
  10. Hiyassat, M. A. S. (2001). Applying modified minimum moment method to multiple resource leveling. Journal of Construction Engineering and Management, 127(3), 192-198. https://doi.org/10.1061/(ASCE)0733-9364(2001)127:3(192)
  11. Jun, D. & El-Rayes, K. (2012). Multiobjective optimization of resource leveling and allocation during construction scheduling, Journal of Construction Engineering and Management, 137(12), 1080-88. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000368
  12. Keane, P. J. & Caletka, A. F. (2015). Delay analysis in construction contracts. John Wiley & Sons, New York.
  13. Leu, S. S. & Hung, T. H. (2002). An optimal construction resource leveling scheduling simulation model. Canadian Journal of Civil Engineering, 29(2), 267-275. https://doi.org/10.1139/l02-007
  14. Li, X. J. Gwak, H. S. & Lee, D. E. (2017). Computational Method for Selecting Optimal Activity Acceleration Methods. Journal of the Architectural Institute of Korea Structure & Construction, 33(6), 57-66 https://doi.org/10.5659/JAIK_SC.2017.33.1.57
  15. Mattila, K. G. & Abraham, D. M. (1998). Resource leveling of linear schedules using integer linear programming. Journal of Construction Engineering and Management, 124(3), 232-244. https://doi.org/10.1061/(ASCE)0733-9364(1998)124:3(232)
  16. Pagnoni, A. (2012). Project engineering: computer-oriented planning and operational decision making. Springer Science & Business Media.
  17. Ponz‐Tienda, J. L. Salcedo‐Bernal, A. & Pellicer, E. (2017a). A Parallel Branch and Bound Algorithm for the Resource Leveling Problem with Minimal Lags. Computer‐Aided Civil and Infrastructure Engineering. 32(6), 474-498. https://doi.org/10.1111/mice.12233
  18. Ponz-Tienda, J. L. Salcedo-Bernal, A. Pellicer, E. & Benlloch-Marco, J. (2017b). Improved Adaptive Harmony Search algorithm for the Resource Leveling Problem with minimal lags. Automation in Construction, 77, 82-92. https://doi.org/10.1016/j.autcon.2017.01.018
  19. Senouci, A. B. & Eldin, N. N. (2004). Use of genetic algorithms in resource scheduling of construction projects. Journal of Construction Engineering and Management, 130(6), 869-877. https://doi.org/10.1061/(ASCE)0733-9364(2004)130:6(869)
  20. Yeniocak, H. (2013). An efficient branch and bound algorithm for the resource leveling problem. Ph.D. dissertation, Middle East Technical University.