The Effect of Price Discount on Time-Cost Trade-off Problem Using Genetic Algorithm
Hadi Mokhtari, Abdollah Aghaie
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DOI: 10.4236/eng.2009.11005   PDF   HTML     6,325 Downloads   11,300 Views   Citations

Abstract

Time-cost trade off problem (TCTP), known in the literature as project crashing problem (PCP) and project speeding up problem (PSP) is a part of project management in planning phase. In this problem, determining the optimal levels of activity durations and activity costs which satisfy the project goal(s), leads to a balance between the project completion time and the project total cost. A large amount of literature has studied this problem under various behavior of cost function. But, in all of them, influence of discount has not been in-vestigated. Hence, in this paper, TCTP would be studied considering the influence of discount on the re-source price, using genetic algorithm (GA). The performance of proposed idea has been tested on a medium scale test problem and several computational experiments have been conducted to investigate the appropriate levels of proposed GA considering accuracy and computational time.

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H. Mokhtari and A. Aghaie, "The Effect of Price Discount on Time-Cost Trade-off Problem Using Genetic Algorithm," Engineering, Vol. 1 No. 1, 2009, pp. 33-40. doi: 10.4236/eng.2009.11005.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] W. Herroelen and R. Leus, “Project scheduling under uncertainty: Survey and research potentials,” European Journal of Operational Research, Vol. 165, pp. 289–306, 2005.
[2] R. A. Bowman, “Stochastic gradient-based time-cost tradeoffs in PERT networks using simulation,” Annals of Operations Research, Vol. 53, pp. 533–551, 1994.
[3] G. Abbasi and A. M. Mukattash, “Crashing PERT networks using mathematical programming,” International Journal of Project Management, Vol. 19, pp. 181–188, 2001.
[4] S. Arisawa and S. E. Elmaghraby, “Optimal time-cost trade-offs in GERT networks,” Management Science, Vol. 18, pp. 589–599, 1972.
[5] L. V. Tavares, “A multi stage non-deterministic model for a project scheduling under resource consideration,” European Journal of Operational Research, Vol. 49, pp. 92–101, 1990.
[6] R. L. Bergman, “A heuristic procedure for solving the dynamic probabilistic project expediting problem,” European Journal of Operational Research, Vol. 192, pp. 125–137, 2009.
[7] S. Foldes and F. Soumis, “PERT and crashing revisited: Mathematical generalization,” European Journal of Operational Research, Vol. 64, pp. 286–294, 1993.
[8] L. Sunde and S. Lichtenberg, “Net-present value cost/ time trade off,” International Journal of Project Management, Vol. 13, pp. 45–49, 1995.
[9] W. J. Gutjahr, C. Strauss and E. Wagner, “A stochastic branch-and-bound approach to activity crashing in project management,” INFORMS Journal on Computing, Vol. 12, pp. 125–135, 2000.
[10] G. Mitchell and T. Klastorin, “An effective methodology for the stochastic project compression problem,” IIE Transaction, Vol. 39, pp. 957–969, 2007.
[11] A. Azaron, C. Perkgoz, and M. Sakawa, “A genetic algorithm approach for the time-cost trade-off in PERT networks,” Applied Mathematics and Computation, Vol. 168, pp. 1317–1339, 2005.
[12] A. Azaron and R. Tavakkoli-Moghaddam, “A multi objective resource allocation problem in dynamic PERT networks,” Applied Mathematics and Computation, Vol. 18, pp. 163–174, 2006.
[13] A. Azaron, H. Katagiri, and M. Sakawa, “Time-cost trade-off via optimal control theory in Markov PERT networks,” Annals of Operations Research, Vol. 150, pp. 47–64, 2007.
[14] P. C. Godinho and J. P. Costa, “A stochastic multimode model for time cost tradeoffs under management flexibility,” OR Spectrum, Vol. 29, pp. 311–334, 2007.
[15] W. Crowston and G. L. Thompson, “Decision CPM: A method for simultaneous planning, scheduling, and control of projects,” Operations Research, Vol. 15, pp. 407–426, 1967.
[16] E. Demeulemeester, S. E. Elmaghraby, and W. Herroelen, “Optimal procedures for the discrete time/cost trade-off problem in project networks,” European Journal of Operational Research, Vol. 88, pp. 50–68, 1996.
[17] E. Demeulemeester, B. De Reyck, B. Foubert, W. Herroelen, and M. Vanhoucke, “New computational results on the discrete time/cost trade-off problem in project networks,” Journal of the Operational Research Society, Vol. 49, pp. 1153–1163, 1998.
[18] D. R. Robinson, “A dynamic programming solution to cost-time tradeoff for CPM,” Management Science, Vol. 22, pp. 158–166, 1975.
[19] M. Vanhoucke and D. Debels, “The discrete time/cost trade-off problem: Extensions and heuristic procedures,” Journal of Scheduling, Vol. 10, pp. 311–326, 2007.
[20] I. Cohen, B. Golany, and A. Shtub, “The stochastic time–cost tradeoff problem: a robust optimization approach,” Networks, Vol. 49, pp. 175–188, 2007.
[21] D. R. Fulkerson, “A network flow computation for project cost curves,” Management Science, Vol. 7, pp. 167–178, 1961.
[22] P. S. Pulat and S. J. Horn, “Time-resource tradeoff problem,” IEEE Transactions on Engineering Management, Vol. 43, pp. 411–417, 1996.
[23] E. B. Berman, “Resource allocation in PERT network under activity continuous time-cost functions,” Management Science, Vol. 10, pp. 734–745, 1964.
[24] R. Lamberson and R. R. Hocking, “Optimum time compression in project scheduling,” Management Science, Vol. 16, pp. B597–B606, 1970.
[25] J. Falk and J. Horowitz, “Critical path problems with concave cost-time curves,” Management Science, Vol. 19, pp. 446–455, 1972.
[26] R. Kelley, “Critical-pathplanning and scheduling: Mathe-matical basis,” Operations Research, Vol. 9, pp. 296–320, 1961.
[27] P. Vrat and C. Kriengkrairut, “A goal programming model for project crashing with piecewise linear time-cost trade-off,” Engineering Costs and Production Economics, Vol. 10, pp. 161–172, 1986.
[28] I. Kaya, “A genetic algorithm approach to determine the sample size for control charts with variables and attributes,” Expert Systems with Applications, Vol. 36, pp. 8719–8734, 2009.

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