Korean Journal of Construction Engineering and Management (한국건설관리학회논문집)

Korea Institute of Construction Engineering and Management (한국건설관리학회)
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Advanced Time-Cost Trade-Off Model using Mixed Integer Programming

혼합정수 프로그래밍 기법을 이용한 진보된 Time-Cost Trade-Off Model

  • Kwon, Obin (Department of Architectural Engineering, Hongik University) ;
  • Lee, Seunghyun (Department of Architectural Engineering, Hongik University) ;
  • Son, Jaeho (Department of Architectural Engineering, Hongik University)
  • Received : 2015.06.04
  • Accepted : 2015.08.26
  • Published : 2015.11.30
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Abstract

Time-Cost Trade-Off (TCTO) model is an important model in the construction project planning and control area. Two types of Existing TCTO model, continuous and discrete TCTO model, have been developed by researchers. However, Using only one type of model has a limitation to represent a realistic crash scenario of activities in the project. Thus, this paper presents a comprehensive TCTO model that combines a continuous and discrete model. Additional advanced features for non-linear relationship, incentive, and liquidated damage are included in the TCTO model. These features make the proposed model more applicable to the construction project. One CPM network with 6 activities is used to explain the proposed model. The model found an optimal schedule for the example to satisfy all the constraints. The results show that new model can represent more flexible crash scenario in TCTO model.

공기비용 트레이드오프 모델은 건설프로젝트의 계획 및 관리에 있어 매우 중요하다. TCTO 모델은 연속모델과 분절모델 두 가지 모델이 개발되어왔다. 그러나 한 종류의 모델만을 사용하여 현실적인 공기단축 시나리오를 적용하기에는 한계가 있다. 이에 TCTO 의 연속적인 모델과, 분절모델을 결합하여 진보된 모델을 제시하였으며 또한, 비선형 관계, 인센티브 및 지체보상금 고려가 가능하도록 TCTO모델에 포함되어 있다. 이런 특성들은 건설프로젝트에 적용가능하다. 6개의 activities로 구성된 CPM 네트워크는 연구에서 제안된 모델을 설명하기 위해 사용되었다. 제시한 모델은 모든 제약 조건을 만족시키는 최적 스케쥴 계산이 가능하다. 결과적으로 본 연구에서 제시한 진보된 TCTO모델은 기존의 모델보다 최적화된 공기단축이 가능하다.

Keywords

References

  1. Baker, B.M. (1997). "Cost/time trade-off analysis for the critical path method: A derivation of the network flow approach" J. Operational Res., 48(12), pp. 1241-1244. https://doi.org/10.1057/palgrave.jors.2600489
  2. Demeulemeester, E., De Reyck, B., Foubert, B., Herroelen, W., and Vanhoucke, M. (1998). "New computational results on the discrete time/ cost trade-off problem in project networks" J. Operational Res., 49(11), pp. 1153-1163. https://doi.org/10.1057/palgrave.jors.2600634
  3. Feng, C. W., Liu, L., and Burns, S. A. (1997). "Using genetic algorithms to solve construction time-cost trade-off problems" J. Comp. in Civ. Engrg., 11(3), pp. 184-189. https://doi.org/10.1061/(ASCE)0887-3801(1997)11:3(184)
  4. Feng, C. W., Liu, L., and Burns, S. A. (2000). "Stochastic construction time-cost trade-off analysis" J. Comp. in Civ. Engrg., 14(2), pp. 117-126. https://doi.org/10.1061/(ASCE)0887-3801(2000)14:2(117)
  5. Hegazy, T. (1999). "Optimization of construction timecost trade-off analysis using genetic algorithms" Can. J. Civ. Engrg., 26(6), pp. 685-697. https://doi.org/10.1139/l99-031
  6. Hegazy, T. and Ersahin, T. (2001). "Simplified spreadsheet solutions. II: Overall schedule optimization" J. Constr. Engrg. And Mgmt., 127(6), pp. 469-475. https://doi.org/10.1061/(ASCE)0733-9364(2001)127:6(469)
  7. Hegazy, T. and Ayed, A. (1999). "Simplified spreadsheet solutions: Models for critical path method and Time-Cost-Tradeoff analysis" Cost Engrg., 41(7), pp. 26-33.
  8. Khang, D. B. and Myint, Y. M. (1999). "Time, cost and quality trade-off in project management: A case study" Int. J. Proj. Mgmt., 17(4), 249-256. https://doi.org/10.1016/S0263-7863(98)00043-X
  9. Kim, M. J., Park, M. S., Lee, H. S., Lee, J. H., and Lee, K. P. (2015) "Development of Manufacturing Planning for Multi Modular Construction Project based on Genetic-Algorithm" Korean journal of Construction Engineering and Management, KICEM, 16(5), pp. 54-64. https://doi.org/10.6106/KJCEM.2015.16.5.054
  10. Leu, S. S. and Yang, C. H. (1999) "GA-based multicriteria optimal model for construction scheduling" J. Constr. Engrg. And Mgmt., 125(5), 420-427. https://doi.org/10.1061/(ASCE)0733-9364(1999)125:6(420)
  11. Leu, S. S., Chen, A.T., and Yang, C. H. (2001). "GAbased fuzzy optimal model for construction timecost trade-off" Int. J. Proj. Mgmt., 19(1), pp. 47-58. https://doi.org/10.1016/S0263-7863(99)00035-6
  12. Li, H., Cao, J. N., and Love, P. (1999). "Using machine learning and GA to solve time-cost trade-off problems" J. Constr. Engrg. And Mgmt., 125(5), pp. 347-353. https://doi.org/10.1061/(ASCE)0733-9364(1999)125:5(347)
  13. Li, H. and Love, P. (1997). "Using improved genetic algorithms to facilitate Time-Cost optimization" J. Constr. Eng. Manage, 123(3), pp. 233-237. https://doi.org/10.1061/(ASCE)0733-9364(1997)123:3(233)
  14. Liu, L., Burns, S. A., and Feng, C. W. (1995). "Construction Tim-Cost Trade-Off Analysis Using LP/IP Hybrid Method" J. Constr. Engrg. And Mgmt., 121(4), pp. 446-454. https://doi.org/10.1061/(ASCE)0733-9364(1995)121:4(446)
  15. Perera, S. (1980), "Linear Programming Solution to Network Compression", ASCE Journal of the Construction Division, 106, pp. 315-327.
  16. Ryu, H. G. and Kim, T. H. (2011) "Analysis of Boundary Conditions for Activities' Relationships in Linear Scheduling Model" Korean journal of Construction Engineering and Management, KICEM, 12(1), pp. 23-32. https://doi.org/10.6106/KJCEM.2011.12.1.23
  17. Stevens, J. D. (1990). Techniques for construction network scheduling. McGraw-Hill, New York.
  18. Winston, W (1997). Operations Research Applications and Algorithms.
  19. Hamdy A. Taha "Operations Research An Introduction" 4th Edition.

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