Selecting high priority activities for the reallocation of resources to reduce construction duration
Abstract
It is difficult to identify economically feasible alternatives to reduce the duration of construction, as many important factors are present in any given construction project, such as increased construction costs and incentives and decreased delay liquidated damages. Most importantly, thousands of activities are interconnected in a complicated manner. This study proposes a method for analyzing the priority of activities for the reallocation of resources in order to reduce construction delay duration. The proposed method is composed of two steps: the prioritization of activities that can reduce construction duration and a reallocation of resources based upon that prioritization. First, in order to analyze priority, combinations of the lowest-cost activities for reducing per day are derived. Then, the importance of influence factors is analyzed, using the fuzzy analytic hierarchy process and fuzzy inference, and priority is derived based on the importance level. Next, the resources are reallocated based on the objective functions of maximizing the importance of the selected activities, reducing the duration, and minimizing the reducing cost. Decision-makers can compare between the reduction duration and available cost, and compare between results of the proposed method and the existing cost-slope method. Then, decision-makers can use the proposed method differently based on their own preferences toward economic and qualitative importance.
Keyword : reallocation of resources, priority of activities, delay liquidated damages, fuzzy analytic hierarchy process, fuzzy inference
How to Cite
Lee, C. (2022). Selecting high priority activities for the reallocation of resources to reduce construction duration. Journal of Civil Engineering and Management, 28(7), 590–600. https://doi.org/10.3846/jcem.2022.17204
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Polat, G., Eray, E., & Bingol, B. N. (2017). An integrated fuzzy MCGDM approach for supplier section problem. Journal of Civil Engineering and Management, 23(7), 926–942. https://doi.org/10.3846/13923730.2017.1343201
Prascevic, N., & Prascevic, Z. (2017). Application of fuzzy AHP for ranking and selection of alternatives in construction project management. Journal of Civil Engineering and Management, 23(8), 1123–1135. https://doi.org/10.3846/13923730.2017.1388278
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Wang, C., Abdul-Rahman, H., & Ch’ng, W. S. (2016). Ant colony optimization (ACO) in scheduling overlapping architectural design activities. Journal of Civil Engineering and Management, 22(6), 780–791. https://doi.org/10.3846/13923730.2014.914100
Yazdani-Chamzini, A. (2014). An integrated fuzzy multi criteria group decision making model for handling equipment selection. Journal of Civil Engineering and Management, 20(5), 660–673. https://doi.org/10.3846/13923730.2013.802714
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Zammori, F. A., Braglia, M., & Frosolini, M. (2009). A fuzzy multi-criteria approach for critical path definition. International Journal of Project Management, 27(3), 278–291. https://doi.org/10.1016/j.ijproman.2008.03.006
Zhou, F., Wang, X., Lim, M. K., He, Y., & Li, L. (2018). Sustainable recycling partner selection using fuzzy DEMATEL-AEW-FVIKOR: A case study in small-and-medium enterprises (SMEs). Journal of Cleaner Production, 196, 489–504. https://doi.org/10.1016/j.jclepro.2018.05.247
Zhou, F., Wang, X., Goh, M., Zhou, L., & He, Y. (2019). Supplier portfolio of key outsourcing parts selection using a two-stage decision making framework for Chinese domestic auto-maker. Computers & Industrial Engineering, 128, 559–575. https://doi.org/10.1016/j.cie.2018.12.014
Zhou, F., Lim, M. K., He, Y., & Pratap, S. (2020). What attracts vehicle consumers’ buying. Industrial Management & Data Systems, 120, 57–78. https://doi.org/10.1108/IMDS-01-2019-0034
Asadi, P., Zeidi, J. R., Mojibi, T., Yazdani-Chamzini, A., & Tamosaitiene, J. (2018). Project risk evaluation by using a new fuzzy model based on Elena guideline. Journal of Civil Engineering and Management, 24(4), 284–300. https://doi.org/10.3846/jcem.2018.3070
Bogus, S. M., Diekmann, J. E., Molenaar, K. R., Harper, C., Patil, S., & Lee, J. S. (2011). Simulation of overlapping design activities in concurrent engineering. Journal of Construction Engineering and Management, 137(11), 950–957. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000363
Castro-Lacouture, D., Süer, G. A., Gonzalez-Joaqui, J., & Yates, J. K. (2009). Construction project scheduling with time, cost, and material restrictions using fuzzy mathematical models and critical path method. Journal of Construction Engineering and Management, 135(10), 1096–1104. https://doi.org/10.1061/(ASCE)0733-9364(2009)135:10(1096)
Dorfeshan, Y., Mousavi, S. M., Mohagheghi, V., & Vahdani, B. (2018). Selecting project-critical path by a new interval type-2 fuzzy decision methodology based on MULTIMOORA, MOOSRA and TPOP methods. Computers & Industrial Engineering, 120, 160–178. https://doi.org/10.1016/j.cie.2018.04.015
Durdyev, S., Ismail, S., & Kandymov, N. (2018). Structural equation model of the factors affecting construction labor productivity. Journal of Construction Engineering and Management, 144(4), 04018007. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001452
El-adaway, I. H., Abotaleb, I. S., Eid, M. S., May, S., Netherton, L., & Vest, J. (2018). Contract administration guidelines for public infrastructure projects in the United States and Saudi Arabia: Comparative analysis approach. Journal of Construction Engineering and Management, 144(6), 04018031. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001472
Federation Internationale Des Ingineurs Conseile. (1999). Conditions of contract for EPC/Turnkey project. Geneva.
García-Nieves, J. D., Ponz-Tienda, J. L., Ospina-Alvarado, A., & Bonilla-Palacios, M. (2019). Multipurpose linear programming optimization model for repetitive activities scheduling in construction projects. Automation in Construction, 105, 102799. https://doi.org/10.1016/j.autcon.2019.03.020
Haj, R. A. A., & El-Sayegh, S. M. (2015). Time–cost optimization model considering float-consumption impact. Journal of Construction Engineering and Management, 141(5), 04015001. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000966
Huang, Y., Zou, X., & Zhang, L. (2016). Genetic algorithm-based method for the deadline problem in repetitive construction projects considering soft logic. Journal of Management in Engineering, 32(4), 04016002. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000426
Ilbahar, E., Kahraman, C., & Cebi, S. (2022). Risk assessment of renewable energy investments: A modified failure mode and effect analysis based on prospect theory and intuitionistic fuzzy AHP. Energy, 239(Part A), 121907. https://doi.org/10.1016/j.energy.2021.121907
Issa, U. H., Mosaad, S. A., & Hassan, M. S. (2019). A model for evaluating the risk effects on construction project activities. Journal of Civil Engineering and Management, 25(7), 687–699. https://doi.org/10.3846/jcem.2019.10531
Lee, C., Lee, C., & Lee, E.-B. (2018). Analysis of the causes and level of maintenance for enterprise systems in construction companies. Journal of Civil Engineering and Management, 24(6), 499–507. https://doi.org/10.3846/jcem.2018.5635
Lin, C.-L., & Lai, Y.-C. (2020). An improved time-cost trade-off model with optimal labor productivity. Journal of Civil Engineering and Management, 26(2), 113–130. https://doi.org/10.3846/jcem.2020.11663
Liu, S.-S., & Wang, C.-J. (2011). Optimizing project selection and scheduling problems with time-dependent resource constraints. Automation in Construction, 20(8), 1110–1119. https://doi.org/10.1016/j.autcon.2011.04.012
Mirahadi, F., & Zayed, T. (2016). Simulation-based construction productivity forecast using Neural-Network-Driven Fuzzy Reasoning. Automation in Construction, 65, 102–115. https://doi.org/10.1016/j.autcon.2015.12.021
Moon, H., Kim, H., Kamat, V. R., & Kang, L. (2015). BIM-based construction scheduling method using optimization theory for reducing activity overlaps. Journal of Computing in Civil Engineering, 29(3), 04014048. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000342
Pan, N.-F. (2008). Fuzzy AHP approach for selecting the suitable bridge construction method. Automation in Construction, 17(8), 958–965. https://doi.org/10.1016/j.autcon.2008.03.005
Polat, G., Eray, E., & Bingol, B. N. (2017). An integrated fuzzy MCGDM approach for supplier section problem. Journal of Civil Engineering and Management, 23(7), 926–942. https://doi.org/10.3846/13923730.2017.1343201
Prascevic, N., & Prascevic, Z. (2017). Application of fuzzy AHP for ranking and selection of alternatives in construction project management. Journal of Civil Engineering and Management, 23(8), 1123–1135. https://doi.org/10.3846/13923730.2017.1388278
Srour, I. M., Abdul-Malak, M.-A. U., Yassine, A. A., & Ramadan, M. (2013). A methodology for scheduling overlapped design activities based on dependency information. Automation in Construction, 29, 1–11. https://doi.org/10.1016/j.autcon.2012.08.001
Wang, C., Abdul-Rahman, H., & Ch’ng, W. S. (2016). Ant colony optimization (ACO) in scheduling overlapping architectural design activities. Journal of Civil Engineering and Management, 22(6), 780–791. https://doi.org/10.3846/13923730.2014.914100
Yazdani-Chamzini, A. (2014). An integrated fuzzy multi criteria group decision making model for handling equipment selection. Journal of Civil Engineering and Management, 20(5), 660–673. https://doi.org/10.3846/13923730.2013.802714
Yilmaz, M. K., Kusakci, A. O., Aksoy, M., & Hacioglu, U. (2022). The evaluation of operational efficiencies of Turkish airports: An integrated spherical fuzzy AHP/DEA approach. Applied Soft Computing, 119, 108620. https://doi.org/10.1016/j.asoc.2022.108620
Zammori, F. A., Braglia, M., & Frosolini, M. (2009). A fuzzy multi-criteria approach for critical path definition. International Journal of Project Management, 27(3), 278–291. https://doi.org/10.1016/j.ijproman.2008.03.006
Zhou, F., Wang, X., Lim, M. K., He, Y., & Li, L. (2018). Sustainable recycling partner selection using fuzzy DEMATEL-AEW-FVIKOR: A case study in small-and-medium enterprises (SMEs). Journal of Cleaner Production, 196, 489–504. https://doi.org/10.1016/j.jclepro.2018.05.247
Zhou, F., Wang, X., Goh, M., Zhou, L., & He, Y. (2019). Supplier portfolio of key outsourcing parts selection using a two-stage decision making framework for Chinese domestic auto-maker. Computers & Industrial Engineering, 128, 559–575. https://doi.org/10.1016/j.cie.2018.12.014
Zhou, F., Lim, M. K., He, Y., & Pratap, S. (2020). What attracts vehicle consumers’ buying. Industrial Management & Data Systems, 120, 57–78. https://doi.org/10.1108/IMDS-01-2019-0034