Using Elitist Particle Swarm Optimization to Facilitate Bicriterion Time-Cost Trade-Off Analysis
Publication: Journal of Construction Engineering and Management
Volume 133, Issue 7
Abstract
The present study develops a new optimization algorithm to find the complete time-cost profile (Pareto front) over a set of feasible project durations, i.e., it solves the time-cost trade-off problem. To improve existing methods, the proposed algorithm aims to achieve three goals: (1) to obtain the entire Pareto front in a single run; (2) to be insensitive to the scales of time and cost; and (3) to treat all existing types of activity time-cost functions, such as linear, nonlinear, discrete, discontinuous, and a hybrid of the above. The proposed algorithm modifies a population-based search procedure, particle swarm optimization, by adopting an elite archiving scheme to store nondominated solutions and by aptly using members of the archive to direct further search. Through a fast food outlet example, the proposed algorithm is shown effective and efficient in conducting advanced bicriterion time-cost analysis. Future applications of the proposed algorithm are suggested in the conclusion.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The writer is indebted to the National Science Council, Taiwan for its financial support (NSC-95-2221-E-032-052-MY3).
References
Alvarez-Benitez, J. E., Everson, R. M., and Fieldsend, J. E. (2005). “A MOPSO algorithm based exclusively on Pareto dominance concepts.” Lecture notes in computer science, Springer, Heidelberg, Germany, 459–473.
Bonabeau, E., and Meyer, C. (2001). “Swarm intelligence: A whole new way to think about business.” Harvard Bus. Rev., 79(5), 107–114.
Chua, D. K. H., Chan, W. T., and Govindan, K. (1997). “A time-cost trade-off model with resource consideration using genetic algorithm.” Civ. Eng. Syst., 14, 291–311.
Coello, C. A. C., Pulido, G. T., and Lechuga, M. S. (2004). “Handling multiple objectives with particle swarm optimization.” IEEE Trans. Evol. Comput., 8(3), 256–279.
De, P., Dunne, E. J., Ghosh, J. B., and Welles, C. E. (1995). “The discrete time-cost trade-off problem revisited.” Eur. J. Oper. Res., 81(2), 225–238.
Deckro, R. F., Hebert, J. E., Verdini, W. A., Grimsrud, P. H., and Venkateshwar, S. (1995). “Nonlinear time/cost trade-off models in project management.” Comput. Ind. Eng., 28(2), 219–229.
Dzeng, R. J., and Lin, Y. C. (2005). “Searching for better negotiation agreement based on genetic algorithm.” Comput. Aided Civ. Infrastruct. Eng., 20(4), 280–293.
Elmaghraby, S. E. (1993). “Resource allocation via dynamic programming in activity networks.” Eur. J. Oper. Res., 64, 199–215.
Engelbrecht, A. P. (2002). Computational intelligence: An introduction, Wiley, New York.
Falk, J., and Horowitz, J. L. (1972). “Critical path problems with concave cost-time curves.” Manage. Sci., 19, 446–455.
Feng, C. W., Liu, L. Y., and Burns, S. A. (1997). “Using genetic algorithms to solve construction time-cost trade-off problems.” J. Comput. Civ. Eng., 11(3), 184–189.
Fieldsend, J. E., Everson, R. M., and Singh, S. (2003). “Using unconstrained elite archives for multi-objective optimization.” IEEE Trans. Evol. Comput., 7(3), 305–323.
Foldes, S., and Soumis, F. (1993). “PERT and crashing revisited: Mathematical generalizations.” Eur. J. Oper. Res., 64, 286–294.
Fulkerson, D. R. (1961). “A network flow computation for project cost curves.” Manage. Sci., 7, 167–178.
Harris, R. B. (1978). Precedence and arrow networking techniques for construction, Wiley, New York, 342–344.
Hegazy, T. (1999). “Optimization of construction time-cost trade-off analysis using genetic algorithms.” Can. J. Civ. Eng., 26(6), 685–697.
Kanda, A., and Singh, N. (1988). “Project crashing with variations in reward and penalty functions: Some mathematical programming formulations.” Eng. Optimiz., 13(4), 307–315.
Kennedy, J., and Eberhart, R. (1995). “Particle swarm optimization.” Proc., 4th IEEE Int. Conf. on Neural Networks, IEEE, Perth, Australia, 1942–1948.
Leu, S. S., and Yang, C. H. (1999). “GA-based multicriteria optimal model for construction scheduling.” J. Constr. Eng. Manage., 125(6), 420–427.
Li, H., Cao, J. N., and Love, P. E. D. (1999). “Using machine learning and GA to solve time-cost trade-off problems.” J. Constr. Eng. Manage., 125(5), 347–353.
Li, H., and Love, P. E. D. (1997). “Improved genetic algorithms for time-cost optimization.” J. Constr. Eng. Manage., 123(3), 233–237.
Liu, L. Y., Burns, S. A., and Feng, C. W. (1995). “Construction time-cost trade-off analysis using LP/IP hybrid method.” J. Constr. Eng. Manage., 121(4), 446–454.
Moder, J. J., Phillips, C. R., and Davis, E. W. (1995). Project management with CPM, PERT, and precedence diagramming, 3rd Ed., Blitz, Middleton, Wis.
Moussourakis, J., and Haksever, C. (2004). “Flexible model for time-cost trade-off problem.” J. Constr. Eng. Manage., 130(3), 307–314.
Phillips, S., and Dessouky, M. I. (1977). “Solving the project time-cost trade-off problem using the minimal cut concept.” Manage. Sci., 24, 393–400.
Reda, R. M., and Carr, R. I. (1989). “Time-cost trade-offs among related activities.” J. Constr. Eng. Manage., 115(3), 475–486.
Shi, Y., and Eberhart, R. C. (1998). “Parameter selection in particle swarm optimization.” Lecture notes in computer science 1447: Evolutionary programming VII, V. W. Porto, N. Saravanan, D. Waagen, and A. E. Eiben, eds., Springer, Berlin, Germany, 591–600.
Skutella, M. (1998). “Approximation algorithms for the discrete time-cost trade-off problem.” Math. Op. Res., 23(4), 909–929.
van den Bergh, F., and Engelbrecht, A. P. (2006). “A study of particle swarm optimization particle trajectories.” Inf. Sci. (N.Y.), 176(8), 937–971.
Wachowiak, M. P., Smolikova, R., Zheng, Y., Zurada, J. M., and Elmaghraby, A. S. (2004). “An approach to multimodal biomedical image registration utilizing particle swarm optimization.” IEEE Trans. Evol. Comput., 8(3), 289–301.
Wolpert, D. H., and Macready, W. G. (1997). “The no free lunch theorems for optimization.” IEEE Trans. Evol. Comput., 1(1), 67–82.
Yang, I. T. (2005a). “Chance-constrained time-cost tradeoff analysis considering funding variability.” J. Constr. Eng. Manage., 131(9), 1002–1012.
Yang, I. T. (2005b). “Impact of budget uncertainty on project time-cost tradeoff.” IEEE Trans. Eng. Manage., 52(2), 167–174.
Zhang, H., Li, X., Li, H., and Huang, F. (2005). “Particle swarm optimization-based schemes for resource-constrained project scheduling.” Autom. Constr., 14(3), 393–404.
Zheng, D. X. M., Ng, S. T., and Kumaraswamy, M. M. (2004). “Applying a genetic algorithm-based multiobjective approach for time-cost optimization.” J. Constr. Eng. Manage., 130(2), 168–176.
Zheng, D. X. M., Ng, S. T., and Kumaraswamy, M. M. (2005). “Applying Pareto ranking and niche formation to genetic algorithm-based multiobjective time-cost optimization.” J. Constr. Eng. Manage., 131(1), 81–91.
Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 133 • Issue 7 • July 2007
Pages: 498 - 505
Copyright
© 2007 ASCE.
History
Received: Jul 20, 2005
Accepted: Dec 19, 2006
Published online: Jul 1, 2007
Published in print: Jul 2007
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.