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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 108
PROCEEDINGS OF THE FIFTEENTH INTERNATIONAL CONFERENCE ON CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING COMPUTING
Edited by: J. Kruis, Y. Tsompanakis and B.H.V. Topping
Paper 275

Time-Cost-Float Optimization in Construction Projects

S.M. El-Sayegh and R. El Haj

Civil Engineering Department, American University of Sharjah, United Arab Emirates

Full Bibliographic Reference for this paper
S.M. El-Sayegh, R. El Haj, "Time-Cost-Float Optimization in Construction Projects", in J. Kruis, Y. Tsompanakis, B.H.V. Topping, (Editors), "Proceedings of the Fifteenth International Conference on Civil, Structural and Environmental Engineering Computing", Civil-Comp Press, Stirlingshire, UK, Paper 275, 2015. doi:10.4203/ccp.108.275
Keywords: optimization, time-cost trade-off, float, project management, risk, construction projects, integer programming.

Summary
Typically, construction projects are constrained by time and money. Contractors aim at completing the project on time to meet contractual requirements, save the indirect cost and release resources to work on new projects. At the same time, contractors try to complete the project within budget in order to realize the profit margin necessary for business continuation. There is a trade-off between time and cost. Time cost trade-off techniques aim at reducing the project duration by crashing critical activities (reducing their duration). When the project duration is reduced, the float available for non-critical activities are reduced which results in reducing the schedule flexibility and increasing the chance of delays in project completion. This is undesirable side effect of the time cost optimization problem. In this paper, we propose a new time cost optimization that includes the cost of float loss in the optimization model. Additionally, we introduce the concept of crashing non-critical activities to increase their float which results in a more flexible schedule. The model uses non-linear integer programming to solve the time cost optimization problem.

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