Abstract
The management problem of projects has received more attention in recent years due to the trend towards increasing complexity in the construction industry. Time, cost and quality are three important aspects of project management. Thus, achieving a balance among the minimum project time, minimum project cost and maximum project quality can determine the success of a construction project. Moreover, the time of a project not only affects the cost but also the quality of the project. However, most research usually ignores the influence of the stochastic environments and considers the time of the project as a constant. Thus, this paper explores a new method to measure the stochastic time based on system reliability theory. Two stochastic time-cost-quality tradeoff optimization models are formulated for two construction projects with considering crossover operations or not, respectively. The optimization of the time reliability-cost-quality tradeoff for the project is achieved by using the particle swarm optimization algorithm. Finally, two illustrative examples are used to demonstrate the effectiveness of the two proposed models for a construction project with four activities.
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Abbreviations
- a 1 :
-
Increasing marginal cost parameter
- C i :
-
The total cost of activity i
- \(C_i^0\) :
-
The direct contract cost of activity i
- \(C_i^D\) :
-
The direct cost of activity i
- \(C_i^I\) :
-
The indirect cost of activity i
- \(C_i^T\) :
-
The tardiness cost of activity i
- t 0 :
-
The total contract time
- T i :
-
The actual time of activity i
- \(T_i^a\) :
-
The tax of activity i
- \(t_i^0\) :
-
The contract time of activity i
- \(t_0^m\) :
-
The sum of the most optimistic time
- \(t_i^m\) :
-
The time of activity i without the impact of environment
- P i :
-
The profit of activity i
- Q i :
-
The quality of activity i
- r 1 :
-
Overhead rate
- r 2 :
-
The profit margin
- r 3 :
-
Tax rate
- r 4 :
-
The reward and punishment parameter per day
- X i :
-
Additional time of activity i due to environmental effects
References
Aminbakhsh S, Sonmez R (2016) Discrete particle swarm optimization method for the large-scale discrete time-cost trade-off problem. Expert Systems with Applications 51(Jun.):177–185, DOI: https://doi.org/10.1016/j.eswa.2015.12.041
Baccarini D (1996) The concept of project complexity-a review. International Journal of Project Management 14(95):201–204, DOI: https://doi.org/10.1016/0263-7863(95)00093-3
Barlow, Richard E (1984) Mathematical theory of reliability: A historical perspective. IEEE Transactions on Reliability R-33(1):16–20, DOI: https://doi.org/10.1109/TR.1984.6448269
Chen JH, Yang LR, Su MC (2009) Comparison of SOM-based optimization and particle swarm optimization for minimizing the construction time of a secant pile wall. Automation in Construction 18(6):844–848, DOI: https://doi.org/10.1016/j.autcon.2009.03.008
Cheng MY, Tran DH (2015) Opposition-based multiple-objective differential evolution to solve the time-cost-environment impact trade-off problem in construction projects. Journal of Computing in Civil Engineering 29(5):04014074, DOI: https://doi.org/10.1061/(ASCE)CP.1943-5487.0000386
Chou SY, Chang YH (2008) A decision support system for supplier selection based on a strategy-aligned fuzzy SMART approach. Expert Systems with Applications 34(4):2241–2253, DOI: https://doi.org/10.1016/j.eswa.2007.03.001
Deckro RF, Hebert JE, Verdini WA, Grimsrud PH, Venkateshwar S (1995) Nonlinear time/cost tradeoff models in project management. Computers & Industrial Engineering 28(2):219–229, DOI: https://doi.org/10.1016/0360-8352(94)00199-W
Fang J, Lai Y (1999) Study on resources optimum allocation of controlling the quality cost in high rise building construction. Journal of Northwestern Institute of Architectural Engineering (1):7–11 (in China)
Huang ZS, Zheng HZ, Chen HG (2006) The fuzzy model for optimizing the allocation of shortening duration in network planning. Fuzzy System and Mathematics 20(4):7, DOI: 1001-7402(2006)04-0151-07
Kalhor E, Khanzadi M, Eshtehardian E, Afshar A (2011) Stochastic time-cost optimization using non-dominated archiving ant colony approach. Automation in Construction 20(8):1193–1203, DOI: https://doi.org/10.1016/j.autcon.2011.05.003
Ke H, Ma W, Ni Y (2009) Optimization models and a GA-based algorithm for stochastic time-cost trade-off problem. Applied Mathematics & Computation 215(1):308–313, DOI: https://doi.org/10.1016/j.amc.2009.05.004
Kelley JE (1959) Critical-path planning and scheduling. Operations Research 9(3):296–320, DOI: https://doi.org/10.1145/1460299.1460318
Kennedy J, Eberhart R (1995) Particle swarm optimization icnn95-international conference on neural networks. IEEE 1995 4:1942–1948, DOI: https://doi.org/10.1109/ICNN.1995.488968
Li YC, Wang S, He YS (2020) Multi-objective optimization of construction project based on improved ant colony algorithm. Tehnički Vjesnik 27(1), DOI: https://doi.org/10.1109/wicom.2010.5601072
Luong DL, Tran DH, Nguyen PT (2018) Optimizing multi-mode time-cost-quality trade-off of construction project using opposition multiple objective difference evolution. International Journal of Construction Management 2018:271–283, DOI: https://doi.org/10.1080/15623599.2018.1526630
Meng XJ, Zhang LX, Pan Y, Liu ZM (2021) Reliability-based multidisciplinary concurrent design optimization method for complex engineering systems. Engineering Optimization 2021:1–21, DOI: https://doi.org/10.1080/0305215X.2021.1928110
Nguyen DT, Doan D, Tran N, Tran DH (2021) A novel multiple objective whale optimization for time-cost-quality tradeoff in non-unit repetitive projects. International Journal of Construction Management 2021(2):1–12, DOI: https://doi.org/10.1080/15623599.2021.1938939
Nguyen DT, Long, LH, Tarigan PB, Tran DH (2021) Tradeoff time cost quality in repetitive construction project using fuzzy logic approach and symbiotic organism search algorithm. Alexandria Engineering Journal 61(2):1499–1518, DOI: https://doi.org/10.1016/j.aej.2021.06.058
Pfeiffer PE (1990) Mathematical expectation. Springer New York, NJ, USA, 15–20
Rajesh A, Varthanan AP, Srikant AJ, Shoban T, Suchith PV (2021) Optimization of shot peening process parameters using PSO algorithm to maximise the fatigue strength. flexural strength and surface hardness of AA2024-T3 alloy. Materials Today: Proceedings 2021(3), DOI: https://doi.org/10.1016/j.matpr.2020.12.1073
Tao R, Tam CM (2012) System reliability optimization model for construction projects via system reliability theory. Automation in Construction 22:340–347, DOI: https://doi.org/10.1016/j.autcon.2011.09.012
Tao R, Tam CM (2013) System reliability theory based multiple-objective optimization model for construction projects. Automation in Construction 31(5):54–64, DOI: https://doi.org/10.1016/j.autcon.2012.11.040
Wang T, Abdallah M, Clevenger C, Monghasemi S (2019) Time-cost-quality trade-off analysis for planning construction projects. Engineering Construction and Architectural Management, ahead-of-print, DOI: https://doi.org/10.1108/ECAM-12-2017-0271
Xu X, Chen X, Liu Z, Yang J, Xu Y, Zhang Y, Gao Y (2021) Multi-objective reliability-based design optimization for the reducer housing of electric vehicles. Engineering Optimization, 1–17, DOI: https://doi.org/10.1080/0305215X.2021.1923704
Zhang L, Du J, Zhang S (2014) Solution to the time-cost-quality tradeoff problem in construction projects based on immune genetic particle swarm optimization. Journal of Management in Engineering 30(2):163–172, DOI: https://doi.org/10.1061/(ASCE)ME.1943-5479.0000189
Zhang H, Xing F (2010) Fuzzy-multi-objective particle swarm optimization for time-cost-quality tradeoff in construction. Automation in Construction 19(8):1067–1075, DOI: https://doi.org/10.1016/j.autcon.2010.07.014
Zhang H, Yu L (2021) Site layout planning for prefabricated components subject to dynamic and interactive constraints. Automation in Construction 126:103693, DOI: https://doi.org/10.1016/j.autcon.2021.103693
Zhu W, Rad HN, Hasanipanah M (2021) A chaos recurrent ANFIS optimized by PSO to predict ground vibration generated in rock blasting. Applied Soft Computing 108:107434, DOI: https://doi.org/10.1016/j.asoc.2021.107434
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This work was supported by the National Natural Science Foundation of China (72201148).
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Wang, J., Wang, Z. & Liu, H. Multi-objective Stochastic Time-cost-quality Optimization for Construction Projects Based on the Reliability Theory. KSCE J Civ Eng 27, 4545–4556 (2023). https://doi.org/10.1007/s12205-023-1083-z
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DOI: https://doi.org/10.1007/s12205-023-1083-z