An improved time-cost trade-off model with optimal labor productivity
Abstract
Optimization of the time-cost trade off (TCT) has received considerable attention for several decades. However, few studies have considered improving performance/productivity of existing crews. To shorten the gap to real-world applications, this study presents an improved TCT model that considers variable productivity using genetic algorithms (GAs). Through an illustrative case and a real world case, the results demonstrate that improving labor productivity of selected activities by allocating existing crews and management can yield an optimized solution. As such, a decision maker can implement a better optimized technique to reduce a project duration under budget while reducing the risk of liquidated damages. The main contribution of this study is to apply managerial improvement of labor productivity to TCT optimization, the project duration can be reduced owing to improved productivity of existing crews rather than inefficient overmanning, overlapping or costly substitution. In the end, three important managerial insights are presented and future research is recommended.
Keyword : labor productivity, time-cost trade-off, optimization, genetic algorithm
How to Cite
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
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Chen, P., & Shahandashti, S. (2009). Hybrid of genetic algorithm and simulated annealing for multiple project scheduling with multiple resource constraints. Automation in Construction, 18, 434-443. https://doi.org/10.1016/j.autcon.2008.10.007
Cho, K., & Hastak, M. (2013). Time and cost-optimized decision support model for fast-track projects. Journal of Construction Engineering and Management, 139(1), 90-101. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000570
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Goldberg, D. E. (1989). Genetic algorithms in search, optimization and machine learning. Addison-Wesley Publishing Co., Inc. Reading, Mass.
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Hegazy, T. (1999). Optimization of construction time-cost tradeoff analysis using genetic algorithms. Canadian Journal of Civil Engineering, 26(6), 685-697. https://doi.org/10.1139/l99-031
Hossain, M., & Chua, D. (2014). Overlapping design and construction activities and an optimization approach to minimize rework. International Journal of Project Management, 32(6), 983-1146. https://doi.org/10.1016/j.ijproman.2013.10.019
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Khoueiry, Y., Srour, I., & Yassine, A. (2013). An optimizationbased model for maximizing the benefits of fast-track construction activities. Journal of the Operational Research Society, 64(1), 1137-1146. https://doi.org/10.1057/jors.2013.30
Klansek, U. (2016). Mixed-integer nonlinear programming model for nonlinear discrete optimization of project schedules under restricted costs. Journal of Construction Engineering and Management, 142(3), 04015088. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001074
Krishnan, V., Eppinger, S., & Whitney, D. (1997). A model-based framework to overlap product development activities. Management Science, 43(4), 437-451. "https://doi.org/10.1287/mnsc.43.4.437
Kuo, M. E. (2013). Cost impact of float loss on a project with time-cost trade-off (PhD thesis). Department of Construction Engineering, National Kaohsiung First University of Science and Technology, Kaohsiung, Taiwan.
Li, H., & Love, P. (1997). Using improved genetic algorithms to facilitate time-cost optimization. Journal of Construction Engineering and Management, 123(3), 233-237. https://doi.org/10.1061/(ASCE)0733-9364(1997)123:3(233)
Mojahed, S., & Aghazadeh, F. (2008). Major factors influencing productivity of water and wastewater treatment plant construction: Evidence from the deep south USA. International Journal of Project Management, 26(2), 195-202. https://doi.org/10.1016/j.ijproman.2007.06.003
Peña-Mora, F., & Li, M. (2001). Dynamic planning and control methodology for design-build fast-track construction projects. Journal of Construction Engineering and Management, 127(1), 1-17. https://doi.org/10.1061/(ASCE)0733-9364(2001)127:1(1)
Roemer, T., & Ahmadi, R. (2004). Concurrent crashing and overlapping in product development. Operations Research, 52(4), 606-622. https://doi.org/10.1287/opre.1040.0125
Rojas, E. M., & Aramvareekul, P. (2003) Labor productivity drivers and opportunities in the construction industry. Journal of Management in Engineering, 19(2), 78-82. https://doi.org/10.1061/(ASCE)0742-597X(2003)19:2(78)
Sanvido, V. E. (1988). Conceptual construction process model. Journal of Construction Engineering and Management, 114(2), 294-310. https://doi.org/10.1061/(ASCE)0733-9364(1988)114:2(294)
Senouci, A., & El-Rayes, K. (2009). Time-profit trade-off analysis for construction projects. Journal of Construction Engineering and Management, 135(8), 718-725. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000031
Thomas, H. (2000). Schedule acceleration, work flow, and labor productivity. Journal of Construction Engineering and Management, 126(4), 261-267. https://doi.org/10.1061/(ASCE)0733-9364(2000)126:4(261)
Thomas, H., & Raynar, K. (1997). Scheduled overtime and labor productivity: Quantitative analysis. Journal of Construction Engineering and Management, 123(2), 181-188. https://doi.org/10.1061/(ASCE)0733-9364(1997)123:2(181)
Thomas, H., & Yiakoumis, I. (1987). Factor model of construction productivity. Journal of Construction Engineering and Management, 113(4), 623-639. https://doi.org/10.1061/(ASCE)0733-9364(1987)113:4(623)
Thomas, H., Sanvido, V., & Sanders, S. (1989). Impact of material management on productivity – A case study. Journal of Construction Engineering and Management, 115(3), 370-384. https://doi.org/10.1061/(ASCE)0733-9364(1989)115:3(370)
Thomas, H., Riley, D., & Sanvido, V. (1999). Loss of labor productivity due to delivery methods and weather. Journal of Construction Engineering and Management, 125(1), 39-46. https://doi.org/10.1061/(ASCE)0733-9364(1999)125:1(39)
Berthaut, F., Pellerin, R., Perrier, N., & Hajji, A. (2011a). Time– cost trade-offs in resource-constraint project scheduling problems with overlapping modes. In CIRRELT-2011-09, Montreal, QC, Canada.
Berthaut, F., Greze, L., Pellerin, R., Perrier, N., & Hajji, A. (2011b). Optimal resource-constraint project scheduling with overlapping modes. In CIRRELT-2011-09, Montreal, QC, Canada.
Chan, W., Chua, D., & Kannan, G. (1996). Construction resource scheduling with genetic algorithms. Journal of Construction Engineering and Management, 122(2), 125-132. https://doi.org/10.1061/(ASCE)0733-9364(1996)122:2(125)
Chen, Y. T. (2011). Assessing the cost impact of float loss on construction projects (PhD thesis). Department of Construction Engineering, National Kaohsiung First University of Science and Technology, Kaohsiung, Taiwan.
Chen, P., & Shahandashti, S. (2009). Hybrid of genetic algorithm and simulated annealing for multiple project scheduling with multiple resource constraints. Automation in Construction, 18, 434-443. https://doi.org/10.1016/j.autcon.2008.10.007
Cho, K., & Hastak, M. (2013). Time and cost-optimized decision support model for fast-track projects. Journal of Construction Engineering and Management, 139(1), 90-101. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000570
Chokor, A., Asmar, M., & Paladugu, B. (2017). Quantifying the impact of cost-based incentives on the performance of building projects in the United States. Journal of Construction Engineering and Management, 22(2), 04016024. https://doi.org/10.1061/(ASCE)SC.1943-5576.0000312
Cristobal, J. (2009). Time, cost, and quality in a road building project. Journal of Construction Engineering and Management, 135(11), 1271-1274. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000094
Dehghan, R., Hazini, K., & Ruwanpura, J. (2015). Optimization of overlapping activities in the design phase of construction projects. Automation in Construction, 59, 81-95. https://doi.org/10.1016/j.autcon.2015.08.004
El-Rayes, K., & Kandil, A. (2005). Time-cost-quality trade-off analysis for highway construction. Journal of Construction Engineering and Management, 131(4), 477-486. https://doi.org/10.1061/(ASCE)0733-9364(2005)131:4(477)
El-Gohary, K., & Aziz, R. (2014). Factors influencing construction labor productivity in Egypt. Journal of Management in Engineering, 30(1), 1-9. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000168
Florez, L., Castro-Lacouture, D., & Medaglia, A. (2013). Sustainable workforce scheduling in construction program management. Journal of the Operational Research Society, 64, 1169-1181. https://doi.org/10.1057/jors.2012.164
Gerk, J., & Qassim, R. (2008). Project acceleration via activity crashing, overlapping, and substitution. IEEE Transactions on Engineering Management, 55(4), 590-601. https://doi.org/10.1109/TEM.2008.927786
Goldberg, D. E. (1989). Genetic algorithms in search, optimization and machine learning. Addison-Wesley Publishing Co., Inc. Reading, Mass.
Hanna, A. S., Russell, J. S., Gotzion, T. W., & Vandenberg, P. J. (1999). The impact of change orders on mechanical construction labour efficiency. Construction Management and Economics, 17(6), 721-730. https://doi.org/10.1080/014461999371060
Hazini, K., Dehghan, R., & Ruwanpura, J. (2013). A heuristic method to determine optimum degree of activity accelerating and overlapping in schedule compression. Canadian Journal of Civil Engineering, 40(4), 382-391. https://doi.org/10.1139/cjce-2012-0380
Hegazy, T. (1999). Optimization of construction time-cost tradeoff analysis using genetic algorithms. Canadian Journal of Civil Engineering, 26(6), 685-697. https://doi.org/10.1139/l99-031
Hossain, M., & Chua, D. (2014). Overlapping design and construction activities and an optimization approach to minimize rework. International Journal of Project Management, 32(6), 983-1146. https://doi.org/10.1016/j.ijproman.2013.10.019
Hossain, M., Chua, D., & Liu, Z. (2012). Optimizing concurrent execution of design activities with minimum redesign. Journal of Computing in Civil Engineering, 26(3), 409-420. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000150
Khoueiry, Y., Srour, I., & Yassine, A. (2013). An optimizationbased model for maximizing the benefits of fast-track construction activities. Journal of the Operational Research Society, 64(1), 1137-1146. https://doi.org/10.1057/jors.2013.30
Klansek, U. (2016). Mixed-integer nonlinear programming model for nonlinear discrete optimization of project schedules under restricted costs. Journal of Construction Engineering and Management, 142(3), 04015088. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001074
Krishnan, V., Eppinger, S., & Whitney, D. (1997). A model-based framework to overlap product development activities. Management Science, 43(4), 437-451. "https://doi.org/10.1287/mnsc.43.4.437
Kuo, M. E. (2013). Cost impact of float loss on a project with time-cost trade-off (PhD thesis). Department of Construction Engineering, National Kaohsiung First University of Science and Technology, Kaohsiung, Taiwan.
Li, H., & Love, P. (1997). Using improved genetic algorithms to facilitate time-cost optimization. Journal of Construction Engineering and Management, 123(3), 233-237. https://doi.org/10.1061/(ASCE)0733-9364(1997)123:3(233)
Mojahed, S., & Aghazadeh, F. (2008). Major factors influencing productivity of water and wastewater treatment plant construction: Evidence from the deep south USA. International Journal of Project Management, 26(2), 195-202. https://doi.org/10.1016/j.ijproman.2007.06.003
Peña-Mora, F., & Li, M. (2001). Dynamic planning and control methodology for design-build fast-track construction projects. Journal of Construction Engineering and Management, 127(1), 1-17. https://doi.org/10.1061/(ASCE)0733-9364(2001)127:1(1)
Roemer, T., & Ahmadi, R. (2004). Concurrent crashing and overlapping in product development. Operations Research, 52(4), 606-622. https://doi.org/10.1287/opre.1040.0125
Rojas, E. M., & Aramvareekul, P. (2003) Labor productivity drivers and opportunities in the construction industry. Journal of Management in Engineering, 19(2), 78-82. https://doi.org/10.1061/(ASCE)0742-597X(2003)19:2(78)
Sanvido, V. E. (1988). Conceptual construction process model. Journal of Construction Engineering and Management, 114(2), 294-310. https://doi.org/10.1061/(ASCE)0733-9364(1988)114:2(294)
Senouci, A., & El-Rayes, K. (2009). Time-profit trade-off analysis for construction projects. Journal of Construction Engineering and Management, 135(8), 718-725. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000031
Thomas, H. (2000). Schedule acceleration, work flow, and labor productivity. Journal of Construction Engineering and Management, 126(4), 261-267. https://doi.org/10.1061/(ASCE)0733-9364(2000)126:4(261)
Thomas, H., & Raynar, K. (1997). Scheduled overtime and labor productivity: Quantitative analysis. Journal of Construction Engineering and Management, 123(2), 181-188. https://doi.org/10.1061/(ASCE)0733-9364(1997)123:2(181)
Thomas, H., & Yiakoumis, I. (1987). Factor model of construction productivity. Journal of Construction Engineering and Management, 113(4), 623-639. https://doi.org/10.1061/(ASCE)0733-9364(1987)113:4(623)
Thomas, H., Sanvido, V., & Sanders, S. (1989). Impact of material management on productivity – A case study. Journal of Construction Engineering and Management, 115(3), 370-384. https://doi.org/10.1061/(ASCE)0733-9364(1989)115:3(370)
Thomas, H., Riley, D., & Sanvido, V. (1999). Loss of labor productivity due to delivery methods and weather. Journal of Construction Engineering and Management, 125(1), 39-46. https://doi.org/10.1061/(ASCE)0733-9364(1999)125:1(39)