A Review for the Multi-Objective Optimization of Time-Cost-Risk Trade-off in Construction

Yazarlar

DOI:

https://doi.org/10.5281/zenodo.14515089

Anahtar Kelimeler:

Time Cost Risk Trade-off, Multi objective optimization, Optimization Algorithms in Construction

Özet

This study explores a multi-objective optimization approach to the Time-Cost-Risk (TCR) trade-off in construction projects, aiming to improve decision-making and project outcomes. The methodology centers on applying advanced optimization algorithms to simultaneously manage the often-conflicting objectives of time, cost, and risk. Through a detailed analysis of various algorithmic approaches, including comparisons of their performance and applicability, this paper demonstrates how these tools can aid in identifying the solutions, where no objective can be improved without compromising another. Case studies from the construction industry illustrate the practical implications of these algorithms, showing how TCR optimization can support more balanced and resilient project planning. This work aims to advance the understanding of multi objective optimization algorithms that approach TCR trade-off, providing a foundation for ongoing improvements in construction project management.

Referanslar

Afshar, A., & Zolfaghar Dolabi, H. R. (2014). Multi-objective optimization of time-cost-safety using genetic algorithm. Iran University of Science & Technology, 4(4), 433-450.

Amoozad Mahdiraji, H., Razavi Hajiagha, S. H., Hashemi, S. S., & Zavadskas, E. K. (2016). A grey multi-objective linear model to find critical path of a project by using time, cost, quality and risk parameters. E a M: Ekonomie a Management, 19(1), 49–61. https://doi.org/10.15240/tul/001/2016-1-004

Anh Nguyen, D., Nguyen, N. T., Tran, Q., & Tran, D. H. (2023). Tradeoff different construction project goals in using a novel multi-objective sea horse algorithm. Alexandria Engineering Journal, 82, 55–68. https://doi.org/10.1016/j.aej.2023.09.059

Askarifard, M., Abbasianjahromi, H., Sepehri, M., & Zeighami, E. (2021). A robust multi-objective optimization model for project scheduling considering risk and sustainable development criteria. Environment, Development and Sustainability, 23(8), 11494–11524. https://doi.org/10.1007/s10668-020-01123-z

Avsar, M. M. S., & Onut, S. (2022). A MULTI-OBJECTIVE MODEL FOR TIME-COST-QUALITY-RISK TRADEOFF PROBLEMS IN PROJECT MANAGEMENT. International Journal of Industrial Engineering : Theory Applications and Practice, 29(6), 826–838. https://doi.org/10.23055/ijietap.2022.29.6.5785

Banihashemi, A., & Khalilzadeh, M. (2022). Time-cost-quality-risk Trade-off Project Scheduling Problem in Oil and Gas Construction Projects: Fuzzy Logic and Genetic Algorithm. In Jordan Journal of Civil Engineering (Vol. 16, Issue 2).

Cheng, J., Yen, G. G., & Zhang, G. (2016). A grid-based adaptive multi-objective differential evolution algorithm. Information Sciences, 367–368, 890–908. https://doi.org/10.1016/j.ins.2016.07.009

Das, S., & Suganthan, P. N. (2011). Differential evolution: A survey of the state-of-the-art. IEEE Transactions on Evolutionary Computation, 15(1), 4–31. https://doi.org/10.1109/TEVC.2010.2059031

Deb, K., & Mohan, M. O. O. U. E. (2001). Wiley-Interscience series in systems and optimization. New York, NY: Wiley-Interscience.

Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), 182-197. https://doi.org/10.1109/4235.996017

Deb, K., & Jain, H. (2014). An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, Part I: Solving problems with box constraints. IEEE Transactions on Evolutionary Computation, 18(4), 577–601. https://doi.org/10.1109/TEVC.2013.2281535

Dorigo, M., Birattari, M., & Stutzle, T. (2006). Ant colony optimization. IEEE Computational Intelligence Magazine, 1(4), 28-39. https://doi.org/10.1109/MCI.2006.329691

Feng, C. W., Liu, L., & Burns, S. A. (1997). Using genetic algorithms to solve construction time-cost trade-off problems. Journal of computing in civil engineering, 11(3), 184-189.

Holland, J. (1975). Adaptation in artificial and natural systems. Ann Arbor: The University of Michigan Press, 232.

Hosseinzadeh, F., Paryzad, B., Pour, N. S., & Najafi, E. (2020). Fuzzy combinatorial optimization in four-dimensional tradeoff problem of cost-time-quality-risk in one dimension and in the second dimension of risk context in ambiguous mode. Engineering Computations (Swansea, Wales), 37(6), 1967–1991. https://doi.org/10.1108/EC-03-2019-0094

Karaboga, D., & Basturk, B. (2008). On the performance of artificial bee colony (ABC) algorithm. Applied soft computing, 8(1), 687-697.

Lakshminarayanan, S., Gaurav, A., & Arun, C. (2010). Multiobjective optimization of time-cost-risk using ant colony optimization. International Journal of Project Planning and Finance, 1(1), 22-38.

Long, L. D., Tran, D. H., & Nguyen, P. T. (2019). Hybrid multiple objective evolutionary algorithms for optimising multi-mode time, cost and risk trade-off problem. International Journal of Computer Applications in Technology, 60(3), 203-214.

Mahmoudi, A., & Feylizadeh, M. R. (2018). A grey mathematical model for crashing of projects by considering time, cost, quality, risk and law of diminishing returns. Grey Systems, 8(3), 272–294. https://doi.org/10.1108/GS-12-2017-0042

Mohammadipour, F., & Sadjadi, S. J. (2016). Project cost-quality-risk tradeoff analysis in a time-constrained problem. Computers and Industrial Engineering, 95, 111–121. https://doi.org/10.1016/j.cie.2016.02.025

Panwar, A., & Jha, K. N. (2021). Integrating Quality and Safety in Construction Scheduling Time-Cost Trade-Off Model. Journal of Construction Engineering and Management, 147(2). https://doi.org/10.1061/(asce)co.1943-7862.0001979

Sharma, K., Soni, A., & Trivedi, M. K. (2023). A Particle Swarm Optimization-Based Model for Quality–Safety Trade-Off Optimization Under Constraint Duration and Cost of Construction Project. Lecture Notes in Mechanical Engineering, 115–126. https://doi.org/10.1007/978-981-19-9285-8_12

Sharma, K., & Trivedi, M. K. (2022). Latin hypercube sampling-based NSGA-III optimization model for multimode resource constrained time–cost–quality–safety trade-off in construction projects. International Journal of Construction Management, 22(16), 3158–3168. https://doi.org/10.1080/15623599.2020.1843769

Sharma, K., & Trivedi, M. K. (2023). Modelling the resource constrained time-cost-quality-safety risk-environmental impact trade-off using opposition-based NSGA III. Asian Journal of Civil Engineering, 24(8), 3083–3098. https://doi.org/10.1007/s42107-023-00696-0

Shishehgarkhaneh, M. B., Azizi, M., Basiri, M., & Moehler, R. C. (2022). BIM-Based Resource Tradeoff in Project Scheduling Using Fire Hawk Optimizer (FHO). Buildings, 12(9). https://doi.org/10.3390/buildings12091472

Sivanandam, S., Deepa, S. (2008). Genetic Algorithm Optimization Problems. In: Introduction to Genetic Algorithms. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73190-0_7

Tran, D. H., & Long, L. D. (2018). Project scheduling with time, cost and risk trade-off using adaptive multiple objective differential evolution. Engineering, Construction and Architectural Management, 25(5), 623–638. https://doi.org/10.1108/ECAM-05-2017-0085

Vijayan, V., Riyana, M. S., & Jayakrishnan, R. (2018). Time-cost-risk optimization in construction work by using ant colony algorithm. International Research Journal of Engineering and Technology, 5(04).

Yılmaz, M., & Dede, T. (2024). Multi-objective time-cost-safety risk trade-off optimization for the construction scheduling problem. Engineering, Construction and Architectural Management. https://doi.org/10.1108/ECAM-02-2024-0249

Yayınlanmış

2024-12-20

Nasıl Atıf Yapılır

Sin, T. S., & Dede, T. (2024). A Review for the Multi-Objective Optimization of Time-Cost-Risk Trade-off in Construction. ISERDAR, 2(3), 54–63. https://doi.org/10.5281/zenodo.14515089

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