Optimal Lighting Arrangements for Nighttime Highway Construction Projects
Publication: Journal of Construction Engineering and Management
Volume 131, Issue 12
Abstract
This paper presents a decision support system for optimizing temporary lighting arrangements in nighttime highway construction projects. The system is developed as a multiobjective genetic algorithm that is capable of: (1) maximizing average illuminance on construction sites; (2) maximizing lighting uniformity in the work zone; (3) minimizing glare to workers and road users; and (4) minimizing lighting costs. The system is designed to support decision makers in their search for practical lighting arrangements that provide various tradeoffs among these four conflicting objectives. Five decision variables are optimized in the present system, namely: number of lighting equipment, equipment positioning, mounting height, aiming angle, and rotation angle. The system is also designed to consider and satisfy all practical constraints that can be encountered in this lighting design problem. An application example is analyzed to illustrate the use of the system and demonstrate its capabilities in generating near optimal and practical lighting arrangements for nighttime highway construction projects.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The writers gratefully acknowledge the financial support provided for this research project by the National Science Foundation CAREER Award under Grant No. NSFCMS 0238470, and by the Illinois Transportation Research Center under Grant No. UNSPECIFIEDTRC-02 VD-H1.
References
Coello, C. (1999). “A comprehensive survey of evolutionary-based multi objective optimization techniques.” Laboratorio Nacional de Informatica Avanzada, Veracruz, Mexico http://www.lania.mx/~ccoello
Deb, K. (2001). Multi-objective optimization using evolutionary algorithms, Wiley, New York.
Ellis, R. D. Jr., and Amos, S. J. (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 bidding method.” J. Constr. Eng. Manage., 127(4), 261–269.
El-Rayes, K., and Hyari, K. (2002). “Automated DSS for lighting design of nighttime operations in highway construction projects.” Proc., 19th International Symp. on Automation and Robotics in Construction, ISARC 2002, National Institute of Standards and Technology, Washington, D.C.
El-Rayes, K., and Hyari, K. (2005). “CONLIGHT: Lighting design model for nighttime highway construction.” J. Constr. Eng. Manage., 131(4), 467–476.
El-Rayes, K., Liu, L., Soibelman, L., and Hyari, K. (2003). “Nighttime construction: Evaluation of lighting for highway construction operations in Illinois.” Final Rep. Project No. VD-H1, FY 00/01, ITRC FR 00/01-2, Illinois Transportation Research Center, Illinois Department of Transportation, Ill.
El-Rayes, K., and Moselhi, O. (2001). “Optimizing resource utilization for repetitive construction projects.” J. Constr. Eng. Manage., 127(1), 18–27.
Feng, C. W., Liu, L., and Burns, S. (1997). “Using genetic algorithms to solve construction time-cost trade-off problems.” J. Comput. Civ. Eng., 11(3), 184–189.
Feng, C. W., Liu, L., and Burns, S. (2000). “Stochastic construction time-cost trade-off analysis.” J. Comput. Civ. Eng., 14(2), 117–126.
Goldberg, D. (1989). Genetic algorithms in search, optimization, and machine learning, Addison Wesley Longman, Inc., Reading, Mass.
Gomar, J., Haas, C., and Morton, D. (2002). “Assignment and allocation optimization of partially multiskilled workforce.” J. Constr. Eng. Manage., 128(2), 103–109.
Hancher, D., and Taylor, T. (2001). “Night-time construction issues.” Proc., Transportation Research Board 80th Annual Meeting, Washington, D.C.
Hegazy, T. (1999). “Optimization of resource allocation and leveling using genetic algorithms.” J. Constr. Eng. Manage., 125(3), 167–175.
Hegazy, T., and Elbeltagi, E. (1999). “EvoSite: Evolution-based model for site layout planning.” J. Comput. Civ. Eng., 13(3), 198–206.
Hegazy, T., and Wassef, N. (2001). “Cost optimization in projects with repetitive nonserial activities.” J. Constr. Eng. Manage., 127(3), 183–191.
Hinze, J., and Carlisle, D. (1990). “Variables impacted by nighttime construction projects.” Final Rep. No. TNW 90-07, Transportation Northwest, Univ. of Washington, Seattle, Wash.
Hyari, K. (2004). “Optimizing lighting conditions for nighttime highway construction operations.” PhD dissertation, Univ. of Illinois at Urbana-Champaign, Urbana, Ill.
Illumination Engineering Society of North America (IESNA). (1998). “IESNA guide for choosing light sources for general lighting.” Rep. No. DG-10-98, New York.
Illuminating Engineering Society of North America (IESNA). (2000). “IESNA practice for roadway lighting.” Rep. No. ANSI/IESNA RP-8-00, American National Standard, New York.
Kumar, A. (1994). “Development of a model for determining work zone illumination requirements during nighttime highway construction.” PhD dissertation, Univ. of Florida, Gainesville, Fla.
McCall, H. C. (1999). “Report on the Department of Transportation’s Administration of the Nighttime Construction Program.” Rep. No. 98-S-50, State of New York Office of the State Comptroller, Albany, N.Y.
Moselhi, O., and El-Rayes, K. (1993). “Scheduling of repetitive projects with cost optimization.” J. Constr. Eng. Manage., 119(4), 681–697.
Price, D. A. (1986). “Nighttime paving.” Implementation Rep. No. CDOH/DTP/R-86/6, Colorado Dept. of Highways, Federal Highway Administration, Denver.
Shepard, F. D., and Cottrel, B. (1985). “Benefits and safety impact of night work-zone activities.” Rep. No. FHWA/RD-85/067, U.S. Department of Transportation, Federal Highway Administration, Washington, D.C.
Pritchard, D. C. (1995). Lighting, 5th Ed., Longman Scientific and Technical, Burnt Mill, Harlow, Essex, United Kingdom.
Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 131 • Issue 12 • December 2005
Pages: 1292 - 1300
Copyright
© 2005 ASCE.
History
Received: Apr 8, 2004
Accepted: May 18, 2005
Published online: Dec 1, 2005
Published in print: Dec 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.