Resource Optimization Using Combined Simulation and Genetic Algorithms
Publication: Journal of Construction Engineering and Management
Volume 129, Issue 6
Abstract
This paper presents a new approach for resource optimization by combining a flow-chart based simulation tool with a powerful genetic optimization procedure. The proposed approach determines the least costly, and most productive, amount of resources that achieve the highest benefit/cost ratio in individual construction operations. To further incorporate resource optimization into construction planning, various genetic algorithms (GA)-optimized simulation models are integrated with commonly used project management software. Accordingly, these models are activated from within the scheduling software to optimize the plan. The result is a hierarchical work-breakdown-structure tied to GA-optimized simulation models. Various optimization experiments with a prototype system on two case studies revealed its ability to optimize resources within the real-life constraints set in the simulation models. The prototype is easy to use and can be used on large size projects. Based on this research, computer simulation and genetic algorithms can be an effective combination with great potential for improving productivity and saving construction time and cost.
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References
Ahuja, H. N., Dozzi, S. P., and Aourizk, S. M. (1984). Project management—Techniques in planning and controlling construction projects, 2nd Ed., Wiley, New York.
Albanese, G. R. Ferris, and Russ, G. S.(1991). “Survey of human resources practices in U.S. construction firms.” J. Constr. Eng. Manage., 7(1), 59–69.
Allam, S. I. G.(1988). “Multi-project scheduling: a new categorization for heuristic scheduling rules in construction scheduling problems.” Constr. Manage. Econom., 6(2), 93–115.
Al-Tabtabai, H., and Alex, A.(1999). “Using genetic algorithms to solve optimization problems in construction.” Eng., Constr., Archit. Manage., 6(2), 121–132.
Burleson, Rebecca C. (1997). “An analysis of multiskilled labor strategies in construction.” Dissertation, Dept. of Civil Engineering. The Univ. of Texas at Austin, Austin, Tex.
Chan, W., Chua, D., and Kannan, G.(1996). “Construction resource scheduling with genetic algorithms.” J. Constr. Eng. Manage., 112(2), 125–132.
Clough, R. H., Sears, G. A., and Sears S. K. (2000). Construction project management, Wiley, New York.
Davis, E. W., and Patterson, J. H.(1975). “A comparison of heuristic and optimum solutions in resource constrained project scheduling.” Manage. Sci., 21(8), 944–955.
Easa, S.(1989). “Resource leveling in construction by optimization.” J. Constr. Eng. Manage., 115(2), 302–316.
Evolver reference manual. (1998). Palisade Corporation, Newfield, N.Y.
Gavish, B., and Pirkul, H.(1991). “Algorithms for multi-resource generalized assignment problem.” Manage. Sci., 37(6), 695–713.
Goldberg, D. E. (1989). Genetic algorithms in search, optimization and machine learning, Addison-Wesley, Reading, Mass.
Halpin, D. W., (1977). “CYCLONE—A method for modeling job site processes.” J. Constr. Div., Am. Soc. Civ. Eng., 103(3), 489–499.
Harris, R. B. (1978). Precedence and arrow networking techniques for construction, John Wiley, New York.
Hegazy, T.(1999). “Optimization of resource allocation and leveling using genetic algorithms.” J. Constr. Eng. Manage., 125(3), 167–175.
Hegazy, T. (2002). Computer-based construction project management, Prentice-Hall, Upper Saddle River, N.J.
Hegazy, T., and El-Zamzamy, H.(1998). “Project management software that meets the challenge.” Cost Eng., 40(5), 25–32.
Hegazy, T., and Moselhi, O.(1994). “Analogy-based solution to markup estimation problem.” J. Comput. Civ. Eng., 8(1), 72–87.
Koumousis, V. K., and Georgiou, P. G.(1994). “Genetic algorithms in discrete optimization of steel truss roofs.” J. Comput. Civ. Eng., 8(3), 309–325.
Li, H., and Love, P.(1997). “Using improved genetic algorithms to facilitate time-cost optimization.” J. Constr. Eng. Manage., 123(3), 233–237.
Liu, L., Burns, S. A., and Feng, C.(1995). “Construction time-cost trade-off analysis using LP/HP hybrid method.” J. Constr. Eng. Manage., 121(4), 446–454.
Microsoft Project. (1998). “Reference manual.” Microsoft Corp., One Microsoft Way, Redmond, Wash.
Moselhi, O., and Lorterapong, P.(1993). “Least impact algorithm for resource allocation.” Can. J. Civ. Eng., 20(2), 180–188.
Paulson, Jr., B. C., Chan, W. T., and Koo, C. C.(1987). “Construction operations simulation by microcomputer.” J. Constr. Eng. Manage., 113(2), 302–314.
Process V3. (2000). User’s guide. Scitor Corporation, Business Solutions Group, 256 Gibraltar Dr., Sunnyvale, Calif.
Shah, K. A., Farid, F., and Baugh, J. W., Jr. (1993). “Optimal resource leveling using integer linear programming.” Proc. 4th Int. Conf. on Computing in Civil and Building Engineering, 1, ASCE, New York.
Talbot, F. B., and Patterson, J. H.(1979). “An efficient integer programming algorithms with net work cuts for solving resource-constrained scheduling problems.” Manage. Sci., 24(11), 1163–1174.
Thomas, R. H.(1991). “Labor productivity and work sampling: The bottom line.” J. Constr. Eng. Manage., 117(3), 423–444.
Wakefield, R., and Sears, G. A.(1997). “Petri nets for simulation and modeling of construction systems.” J. Constr. Eng. Manage., 123(2), 105–112.
Zaneldin, E., and Hegazy, T. (1998). Flowchart-based simulation of construction operations, 1988 AACE International Transactions, Cincinnati, IT/IM.08.01-IT/IM.08.06.
Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 129 • Issue 6 • December 2003
Pages: 698 - 705
Copyright
Copyright © 2003 American Society of Civil Engineers.
History
Received: Nov 20, 2001
Accepted: Oct 10, 2002
Published online: Nov 14, 2003
Published in print: Dec 2003
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