Tradeoff time cost quality in repetitive construction project using fuzzy logic approach and symbiotic organism search algorithm
Time cost and quality are three important factors in planning and controlling construction projects. Getting these factors in balance, which minimizes the project duration, the total project cost, and maximizes the total quality could define the success of a construction project. Aside from planning...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Elsevier
2022
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/5b71f00f54154418b931f374a424f231 |
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| Sumario: | Time cost and quality are three important factors in planning and controlling construction projects. Getting these factors in balance, which minimizes the project duration, the total project cost, and maximizes the total quality could define the success of a construction project. Aside from planning and estimating the project properly, a consideration of uncertainty while implementing the project is needed to represent a more realistic outcome for time, cost, and quality trade-off (TCQT) problem in construction projects. In this paper, fuzzy logic is utilized to model the uncertainty embedding α-cut approach to see the effect of the uncertainty on the time, cost, and quality of the project. Then multi-objective Symbiotic Organism Search (SOS) algorithm is applied to find a set of the optimal solution in different uncertainty levels and provide the project manager several possible actions to implement the project. Two numerical case studies of a repetitive construction project were analyzed to see the effectiveness of the model and its capability to solve the TCQT problem in the construction project. The results showed that the proposed model is powerful to explore the solution for the shortest project duration with minimum incurred cost and high overall quality in the construction project. In comparison to the other widely used methods and other algorithms, the proposed model is proven to be effective and competitive in solving the TCQT problem. |
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