A Preemptive multimode resource constrained project scheduling model with cash flows

Document Type : Research Paper

Authors

1 Department of Industrial Engineering, Islamic Azad University, Markazi Province, AraK, Iran

2 Arak University of Technology, Arak, Iran

Abstract

Resource constrained project scheduling problem is one of the most important issues in project planning and management. The objective function of this problem is to minimize the completion time of a project. When there is budget constraint or high risk for investment, using the criteria such as cash flows is so important. The development of computer systems and processors makes it possible to take more assumptions into modeling to obtain robust optimal solution. Recent research has been conducted on multimode resource constrained project scheduling problem with preemptive activities (P-MRCPSP). Assuming preemption of activities causes the model to approach the real-world problems in project scheduling. This assumption may occur due to factors such as equipment failure and shortage of resources.
In most of the previous studies, the change in mode of activities was not possible after the discontinuation. In this paper, it is assumed that each activity can continue in various modes of operation after a stop. The developed model aims to minimize project completion time and maximize cash flow of the project, simultaneously. Two algorithms, i.e. Simulated Annealing (SA) and Multiple Objective Particle Swarm Optimization (MOPSO) have been developed to solve the proposed model. The obtained results of these two algorithms show that SA algorithm has the better performance.

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Abramson, D., Krishnamoorthy, M., & Dang, H. (1999). Simulated annealing cooling schedules for the school timetabling problem. Asia Pacific Journal of Operational Research16, 1-22.
 
Afshar-Nadjafi, B. (2018). A solution procedure for preemptive multi-mode project scheduling problem with mode changeability to resumption. Applied Computing and Informatics14(2), 192-201.
 
Blazewicz, J., Lenstra, J. K., & Kan, A. R. (1983). Scheduling subject to resource constraints: classification and complexity. Discrete applied mathematics5(1), 11-24.
 
Buddhakulsomsiri, J., & Kim, D. S. (2006). Properties of multi-mode resource-constrained project scheduling problems with resource vacations and activity splitting. European Journal of Operational Research175(1), 279-295.
 
Coello, C. A. C., Lamont, G. B., & Van Veldhuizen, D. A. (2007). Evolutionary algorithms for solving multi-objective problems (Vol. 5). New York: Springer.
 
Damak, N., Jarboui, B., Siarry, P., & Loukil, T. (2009). Differential evolution for solving multi-mode resource-constrained project scheduling problems. Computers & Operations Research36(9), 2653-2659.
 
De Reyck, B., & Herroelen, W. (1999). The multi-mode resource-constrained project scheduling problem with generalized precedence relations. European Journal of Operational Research119(2), 538-556.
 
Grinold, R. C. (1972). The payment scheduling problem. Naval Research Logistics Quarterly19(1), 123-136.
Hartmann, S., & Briskorn, D. (2010). A survey of variants and extensions of the resource-constrained project scheduling problem. European Journal of operational research207(1), 1-14.
 
Hill, A., Lalla-Ruiz, E., Voß, S., & Goycoolea, M. (2018). A multi-mode resource-constrained project scheduling reformulation for the waterway ship scheduling problem. Journal of scheduling, 1-10.
 
Kirkpatrick Jr, S. CDG, and Vecchi, MP (1983). Optimizing by simulated annealing. Science, 671-680.
Kolisch, R., & Sprecher, A. (1997). PSPLIB-a project scheduling problem library: OR software-ORSEP operations research software exchange program. European journal of operational research96(1), 205-216.
 
Mori, M., & Tseng, C. C. (1997). A genetic algorithm for multi-mode resource constrained project scheduling problem. European Journal of Operational Research100(1), 134-141.
 
Russell, A. H. (1970). Cash flows in networks. Management Science16(5), 357-373.
 
Van Peteghem, V., & Vanhoucke, M. (2010). A genetic algorithm for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problem. European Journal of Operational Research201(2), 409-418.