TECHNICAL PAPERS
Aug 1, 2008

New Mathematical Optimization Model for Construction Site Layout

Publication: Journal of Construction Engineering and Management
Volume 134, Issue 8

Abstract

Layout of temporary construction facilities (objects) is an important activity during the planning process of construction projects. The construction area layout is a complex problem whose solution requires the use of analytical models. Existing popular models employ genetic algorithms that have proven to be useful tools in generating near optimal site layouts. This paper presents an alternative approach based on mathematical optimization that offers several important features and generates a global optimal solution. The construction area consists of an unavailable area that includes existing facilities (sites) and available area in which the objects can be located. The available area is divided into regions that are formulated using binary variables. The locations of the objects are determined by optimizing an objective function subject to a variety of physical and functional constraints. The objective function minimizes the total weighted distance between the objects and the sites as well as among the objects (if desired). The distance can be expressed as Euclidean or Manhattan distance. Constraints that ensure objects do not overlap are developed. The new approach, which considers a continuous space in locating the objects simultaneously, offers such capabilities as accommodating object adjacency constraints, facility proximity constraints, object–region constraints, flexible orientation of objects, visibility constraints, and nonrectangular objects, regions, and construction areas. Application of the model is illustrated using two examples involving single and multiple objects. The proposed model is efficient and easy to apply, and as such should be of interest to construction engineers and practitioners.

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References

Cheng, M. Y., and O’Connor, J. T. (1996). “ArcSite: Enhanced GIS for construction site layout.” J. Constr. Eng. Manage., 122(4), 329–336.
Deb, K. (2001). Multiobjective optimization using evolutionary algorithms, Wiley, New York.
Easa, S. M. (1989). “Resource levelling in construction by optimization.” J. Constr. Eng. Manage., 115(2), 302–316.
Easa, S. M., Sadeghpour, F., and Hossain, K. M. A. (2006). “New optimization approach for construction site layout.” Proc., Annual Conf. of the Canadian Society for Civil Engineering, CSCE, Calgary, Alta, Canada.
Elbeltagi, E., Hegazy, T., and Eldosouky, A. (2004). “Dynamic layout of construction temporary facilities considering safety.” J. Constr. Eng. Manage., 130(4), 534–541.
Elbeltagi, E., Hegazy, T., Hosny, H., and Eldosouky, A. (2001). “Schedule-dependent evolution of site layout planning.” Constr. Manage. Econom., 19(7), 689–697.
Frontline Systems, Inc. (2005). Premium solver platform—User’s guide, frontline solvers, Incline Village, Nev.
Hamiani, A., and Popescu, C. (1988). “CONSITE: A knowledge-based expert system for site layout.” Proc., Computers in Civil Engineering, ASCE, New York, 248–256.
Hegazy, T. M., and Elbeltagi, E. (1999). “EvoSite: Evolution-based model for site layout planning.” J. Comput. Civ. Eng., 13(3), 198–206.
Khalafallah, A., and El-Rayes, K. (2006). “Minimizing construction-related hazards in airport expansion projects.” J. Constr. Eng. Manage., 132(6), 562–572.
Li, H., and Love, P. E. D. (1998). “Site-level facilities layout using genetic algorithms.” J. Comput. Civ. Eng., 12(4), 227–231.
Mawdesley, M., Al-jibouri, S., and Yang, H. (2002). “Genetic algorithms for construction site layout in project planning.” J. Constr. Eng. Manage., 128(5), 418–426.
Palisade Europe. (2006). “Evolver: The innovative optimizer for windows.” http://www.palisade-europe.com/evolver/ (August 18, 2007).
Sadeghpour, F. (2004). “A CAD-based model for site layout.” Ph.D. dissertation, Concordia Univ., Montreal.
Sadeghpour, F., Moselhi, O., and Alkass, S. (2006). “Computer-aided site layout planning.” J. Constr. Eng. Manage., 132(2), 143–151.
Schrage, L. (2006). Optimization modeling with LINGO, LINDO Systems, Palo Alto, Calif.
Tam, C. M., Tong, T. K., Leung, A. W., and Chiu, G. W., (2002). “Site layout planning using nonstructural fuzzy decision support system.” J. Constr. Eng. Manage., 128(3), 220–231.
Tommelein, I. D., Levitt, R. E., and Hayes-Roth, B. (1992). “Site layout modeling: How can artificial intelligence help?” J. Constr. Eng. Manage., 118(3), 594–611.
Yeh, I. (1995). “Construction-site layout using annealed neural network.” J. Comput. Civ. Eng., 9(3), 201–208.
Zouein, P. P. (1995). “MoveSchedule: A planning tool for scheduling space use on construction sites.” Ph.D. dissertation, Univ. of Michigan, Ann Arbor, Mich.
Zouein, P. P., Hamanani, H., and Hajar, A. (2002). “Genetic algorithm for solving site layout problem with unequal-size and constrained facilities.” J. Comput. Civ. Eng., 16(2), 143–151.
Zouein, P. P., and Tommelein, I. D. (1999). “Dynamic layout planning using a hybrid incremental solution method.” J. Constr. Eng. Manage., 125(6), 400–408.
Zouein, P. P., and Tommelein, I. D. (2001). “Improvement algorithm for limited space scheduling.” J. Constr. Eng. Manage., 127(2), 116–124.

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Go to Journal of Construction Engineering and Management
Journal of Construction Engineering and Management
Volume 134Issue 8August 2008
Pages: 653 - 662

History

Received: Aug 30, 2006
Accepted: Nov 5, 2007
Published online: Aug 1, 2008
Published in print: Aug 2008

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Authors

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Said M. Easa, M.ASCE
Professor, Dept. of Civil Engineering, Ryerson Univ., Toronto ON, Canada M5B 2K3. E-mail: [email protected]
K. M. A. Hossain, M.ASCE
Associate Professor, Dept. of Civil Engineering, Ryerson Univ., Toronto ON, Canada M5B 2K3. E-mail: [email protected]

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