The Effect of Price Discount on Time-Cost Trade-off Problem Using Genetic Algorithm

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DOI: 10.4236/eng.2009.11005    6,036 Downloads   10,908 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.

Cite this paper

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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