Time-Cost-Quality Trade-Off Analysis for Highway Construction
Publication: Journal of Construction Engineering and Management
Volume 131, Issue 4
Abstract
Many departments of transportation have recently started to utilize innovative contracting methods that provide new incentives for improving construction quality. These emerging contracts place an increasing pressure on decision makers in the construction industry to search for an optimal resource utilization plan that minimizes construction cost and time while maximizing its quality. This paper presents a multiobjective optimization model that supports decision makers in performing this challenging task. The model is designed to transform the traditional two-dimensional time-cost tradeoff analysis to an advanced three-dimensional time-cost-quality trade-off analysis. The model is developed as a multiobjective genetic algorithm to provide the capability of quantifying and considering quality in construction optimization. An application example is analyzed to illustrate the use of the model and demonstrate its capabilities in generating and visualizing optimal tradeoffs among construction time, cost, and quality.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgment
The writers gratefully acknowledge the financial support provided by the National Science Foundation for this research project under the CAREER Award CMS-0238470.
References
Adeli, H., and Karim, A. (1997). “Scheduling/cost optimization and neural dynamics model for construction projects,” J. Constr. Eng. Manage., 123(4), 450–458.
American Society of Civil Engineers (ASCE). (2002). “Report card: Reports and statistics.” ⟨http://www.asce.org/reportcard/⟩.
American Society for Testing and Materials (ASTM). (2003a). “Standard test method for compressive strength of cylindrical concrete specimens.” C 39/C 39M-01, West Conshohocken, Pa.
American Society for Testing and Materials (ASTM). (2003b). “Standard test method for conducting subjective pavement ride quality ratings.” E 1927-98, West Conshohocken, Pa.
Anderson, A., and Russell, J. (2001). “Guidelines for warranty, multiparameter, and best value contracting.” NCHRP Rep. No. 451, National Cooperative Highway Research Program, Washington, D.C.
Burns, S., Liu, L., and Feng, C. (1996) “The LP/IP hybrid method for construction time-cost trade-off analysis.” Constr. Manage. Econom., 14, 265–276.
California Department of Transportation (Caltrans). (2001). “Construction manual.” ⟨http://www.dot.ca.gov/hq/construc/manual2001/⟩, (June 11, 2003).
Chan, W., Chua, D., and Kannan, G. (1996). “Construction resource scheduling with genetic algorithms.” J. Constr. Eng. Manage., 122(2), 125–132.
Deb, K. (2001). Multiobjective optimization using evolutionary algorithms, Wiley, New York.
Deb, K., Agrawal, S., Pratap, A., and Meyarivan, T. (2001). “A fast elitist nondominated sorting genetic algorithm for multiobjective optimization.” KANGAL Rep. No. 200001, Genetic Algorithm Laboratory, Indian Institute of Technology, Kanpur, India.
Easa, S. (1989). “Resource leveling in construction by optimization.” J. Constr. Eng. Manage., 115(2), 302–316.
Ellis, R., and Amos, S. (1996). “Development of work zone lighting standards for nighttime highway work.” Transportation Research Record 1529, Transportation Research Board, Washington, D.C.
El-Rayes, K. (2001). “Optimum planning of highway construction under the A+B bidding method.” J. Constr. Eng. Manage., 127(4), 261–269.
El-Rayes, K., and Moselhi, O. (2001). “Optimizing resource utilization for repetitive construction projects.” J. Constr. Eng. Manage., 127(1), 18–27.
El-Rayes, K., and Hyari, K. (2002). “Automated DSS for lighting design of nighttime operations in highway construction projects.” Proc., 19th Int. Symp. on Automation and Robotics in Construction.
El-Rayes, K., and Hyari, K. (2004). “CONLIGHT: Lighting design model for nighttime highway construction.” J. Constr. Eng. Manage., 131(4), 467.
Engineering News Record (ENR). (2002). “Springfield mixing bowl tosses up a medley of challenges: Virginia DOT and contractors strive to untangle I-15 web.”
Federal Highway Administration (FHWA). (2000). “Highway statistics 2000.” Office of Highway Policy Information, FHWA, U.S. Dept. of Transportation, Washington, D.C.
Feng, C., Liu, L., and Burns, S. A. (1997). “Using genetic algorithms to solve construction time-cost trade-off problems.” J. Comput. Civ. Eng., 11(3), 184–189.
Feng, C., Liu, L., and Burns, S. (2000). “Stochastic construction time-cost trade-off analysis.” J. Comput. Civ. Eng., 14(2), 117–126.
Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning, Addison–Wesley, New York.
Gomar, J., Haas, C., and Morton, D. (2002). “Assignment and allocation optimization of partially multiskilled workforce.” J. Constr. Eng. Manage., 128(2), 103–109.
Hegazy, T. (1999). “Optimization of resource allocation and leveling using genetic algorithms.” J. Constr. Eng. Manage., 125(3), 167–175.
Hegazy, T., and Ersahin, T. (2001). “Simplified spreadsheet solutions. II: Overall schedule optimization.” J. Constr. Eng. Manage., 127(6), 469–475.
Hegazy, T., and Wassef, N. (2001). “Cost optimization in projects with repetitive nonserial activities.” J. Constr. Eng. Manage., 127(3), 183–191.
Herbsman, Z. (1995). “A+B bidding method—Hidden success story for highway construction.” J. Constr. Eng. Manage., 121(4), 430–437.
Illinois Department of Transportation (IDOT). (2002). “2002 construction manual.” ⟨http://www.dot.state.il.us/constructionmanual/preface.html⟩ (June 11, 2003).
Jaraiedi, M., Plummer, R., and Aber, M. (1995). “Incentive/disincentive guidelines for highway construction contracts.” J. Constr. Eng. Manage., 121(1), 112–120.
Leu, S., and Hwang, S. (2001). “Optimal repetitive scheduling model with shareable resource constraint.” J. Constr. Eng. Manage., 127(4), 270–280.
Li, H., and Love, P. (1997). “Using improved genetic algorithms to facilitate time-cost optimization.” J. Constr. Eng. Manage., 123(3), 233–237.
Li, H., Cao, J., and Love, P. (1999). “Using machine learning and genetic algorithm to solve time-cost trade-off problems.” J. Constr. Eng. Manage., 125(5), 347–353.
Maxwell, D., Back, E., and Toon, J. (1998). “Optimization of crew configurations using activity-based costing.” J. Constr. Eng. Manage., 124(2), 162–168.
Meredith, D., Kam, W., Woodhead, R., and Wortman, R. (1985). Design and planning of engineering systems, Prentice–Hall, Englewood Cliffs, N.J.
Moselhi, O., and El-Rayes, K. (1993). “Scheduling of repetitive projects with cost optimization.” J. Constr. Eng. Manage., 119(4), 681–697.
Minchin, R. E., and Smith, G. R. (2001). “Quality-based performance rating of contractors for prequalification and bidding purposes.” PTI 2001-25, The Pennsylvania Transportation Institute, The Pennsylvania State Univ., University Park, Pa.
RSMeans. (2000). Heavy construction cost data: 14th annual edition, Kingston, Mass.
Senouci, A., and Eldin, N. (1996). “Dynamic programming approach to scheduling of nonserial linear project.” J. Comput. Civ. Eng., 10(2), 106–114.
U.S. Department of Transportation (USDOT). (2000). “1999 status of the nation’s highways, bridges and transit: Conditions and performance.” Rep. to Congress, Federal Highway Administration, Federal Transit Administration, Washington, D.C.
Zitzler, E., Laumanns, M., and Thiele, L. (2001). “SPEA2: Improving the strength Pareto evolutionary algorithm.” TIK-Rep. No. 103, Swiss Federal Institute of Technology, (ETH), Zurich, Switzerland.
Information & Authors
Information
Published In
Copyright
© 2005 ASCE.
History
Received: Jun 19, 2003
Accepted: Jun 18, 2004
Published online: Apr 1, 2005
Published in print: Apr 2005
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.