Skip to main content
SpringerLink
Log in

An applicable method for modifying over-allocated multi-mode resource constraint schedules in the presence of preemptive resources

  • Original-OR Modeling/Case Study
  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

The issue resource over-allocating is a big concern for project engineers in the process of scheduling project activities. Resources over-allocating are frequently seen after scheduling of a project in practice which causes the schedule to be useless. Modifying an over-allocated schedule is very complicated and needs a lot of efforts and time. In this research a new method is developed for modifying over-allocated schedules in multi-mode resource constrained project scheduling problems with positive cash flows (MRCPSP-PDC). The aim is maximizing net present value of the MRCPSPs (or logically minimizing negative cash flows). The proposed method is designed to consider all types of activity precedence including Finish to Start, Start to Start, Finish to Finish and Start to Finish and also lags between activities. It can also be used alone or as a macro in Microsoft Office Project\(^{\textregistered }\) Software to modify resource over-allocated days after scheduling a project. In this research progress payment method and preemptive resources are considered. The proposed approach maximizes NPV by scheduling activities through the resource calendar respecting to the available level of pre-emptive resources and activity numbers. To examine the performance of the proposed method a number of experiments that is derived from the literature are solved. The results are then compared with the state where resource constraints are relaxed and also Simulated Annealing algorithm. The outcomes show that the proposed algorithm can provide modified schedules with no over-allocated days for experiment with 1000 activities and 100 preemptive resources in a few seconds. The method is then applied for scheduling a manufacturing project in practice.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22

Similar content being viewed by others

Notes

  1. As mentioned before, all cash flow data are kept secret by the request of the company. For this purpose, the cash flows are changed in a logic manner.

References

  • Abbasi, B., Shadrokh, S., & Arkat, J. (2006). Bi-objective resource-constrained project scheduling with robustness and makespan criteria. Applied Mathematics and Computation, 180(1), 146–152.

    Article  Google Scholar 

  • Achuthan, N., & Hardjawidjaja, A. (2001). Project scheduling under time dependent costs-A branch and bound algorithm. Annals of Operations Research, 108(1–4), 55–74.

    Article  Google Scholar 

  • Alcaraz, J., & Maroto, C. (2001). A robust genetic algorithm for resource allocation in project scheduling. Annals of Operations Research, 102(1–4), 83–109.

    Article  Google Scholar 

  • Ballestín, F., Valls, V., & Quintanilla, S. (2008). Pre-emption in resource-constrained project scheduling. European Journal of Operational Research, 189(3), 1136–1152.

    Article  Google Scholar 

  • Baroum, S. M., & Patterson, J. H. (1999). An exact solution procedure for maximizing the net present value of cash flows in a network project scheduling. Berlin: Springer.

    Google Scholar 

  • 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 Research, 175(1), 279–295.

    Article  Google Scholar 

  • Castejón-Limas, M., Ordieres-Meré, J., González-Marcos, A., & González-Castro, V. (2011). Effort estimates through project complexity. Annals of Operations Research, 186(1), 395–406.

    Article  Google Scholar 

  • Chtourou, H., & Haouari, M. (2008). A two-stage-priority-rule-based algorithm for robust resource-constrained project scheduling. Computers & Industrial Engineering, 55(1), 183–194.

    Article  Google Scholar 

  • Damay, J., Quilliot, A., & Sanlaville, E. (2007). Linear programming based algorithms for preemptive and non-preemptive RCPSP. European Journal of Operational Research, 182(3), 1012–1022.

    Article  Google Scholar 

  • De Reyck, B. (1998). A branch-and-bound procedure for the resource-constrained project scheduling problem with generalized precedence relations. European Journal of Operational Research, 111(1), 152–174.

    Article  Google Scholar 

  • Delgoshaei, A., Ariffin, M. K., Baharudin, B. H. T. B., & Leman, Z. (2014). A backward approach for maximizing net present value of multi-mode pre-emptive resource-constrained project scheduling problem with discounted cash flows using simulated annealing algorithm. International Journal of Industrial Engineering and Management, 5(3), 151–158.

    Google Scholar 

  • Delgoshaei, A., Ariffin, M. K. M., Baharudin, B. H. T. B. & Leman, Z. (2015). Minimizing makespan of a resource-constrained scheduling problem: A hybrid greedy and genetic algorithms. Resource.

  • Demeulemeester, E. L., & Herroelen, W. S. (1996). An efficient optimal solution procedure for the preemptive resource-constrained project scheduling problem. European Journal of Operational Research, 90(2), 334–348.

    Article  Google Scholar 

  • Elmaghraby, S. E., & Herroelen, W. S. (1990). The scheduling of activities to maximize the net present value of projects. European Journal of Operational Research, 49(1), 35–49.

    Article  Google Scholar 

  • Hartmann, S. (2001). Project scheduling with multiple modes: A genetic algorithm. Annals of Operations Research, 102(1–4), 111–135.

    Article  Google Scholar 

  • Hartmann, S., & Briskorn, D. (2010). A survey of variants and extensions of the resource-constrained project scheduling problem. European Journal of Operational Research, 207(1), 1–14.

    Article  Google Scholar 

  • Icmeli, O., & Erenguc, S. S. (1994). A tabu search procedure for the resource constrained project scheduling problem with discounted cash flows. Computers & Operations Research, 21(8), 841–853.

    Article  Google Scholar 

  • Icmeli, O., Erenguc, S. S., & Zappe, C. J. (1993). Project scheduling problems: A survey. International Journal of Operations & Production Management, 13(11), 80–91.

    Article  Google Scholar 

  • Jarboui, B., Damak, N., Siarry, P., & Rebai, A. (2008). A combinatorial particle swarm optimization for solving multi-mode resource-constrained project scheduling problems. Applied Mathematics and Computation, 195(1), 299–308.

    Article  Google Scholar 

  • Ke, H., & Liu, B. (2010). Fuzzy project scheduling problem and its hybrid intelligent algorithm. Applied Mathematical Modelling, 34(2), 301–308.

    Article  Google Scholar 

  • Kelley, J. E. (1963). The critical-path method: Resources planning and scheduling. Industrial Scheduling, 13, 347–365.

    Google Scholar 

  • Kim, K., Yun, Y., Yoon, J., Gen, M., & Yamazaki, G. (2005). Hybrid genetic algorithm with adaptive abilities for resource-constrained multiple project scheduling. Computers in Industry, 56(2), 143–160.

    Article  Google Scholar 

  • Kolisch, R. (1996). Serial and parallel resource-constrained project scheduling methods revisited: Theory and computation. European Journal of Operational Research, 90(2), 320–333.

    Article  Google Scholar 

  • Kolisch, R., & Drexl, A. (1997). Local search for nonpreemptive multi-mode resource-constrained project scheduling. IIE Transactions, 29(11), 987–999.

    Google Scholar 

  • Laslo, Z. (2010). Project portfolio management: An integrated method for resource planning and scheduling to minimize planning/scheduling-dependent expenses. International Journal of Project Management, 28(6), 609–618.

    Article  Google Scholar 

  • Lee, C. Y., & Lei, L. (2001). Multiple-project scheduling with controllable project duration and hard resource constraint: Some solvable cases. Annals of Operations Research, 102(1–4), 287–307.

    Article  Google Scholar 

  • Lova, A., & Tormos, P. (2001). Analysis of scheduling schemes and heuristic rules performance in resource-constrained multiproject scheduling. Annals of Operations Research, 102(1–4), 263–286.

    Article  Google Scholar 

  • Mika, M., Waligóra, G., & Węglarz, J. (2005). Simulated annealing and tabu search for multi-mode resource-constrained project scheduling with positive discounted cash flows and different payment models. European Journal of Operational Research, 164(3), 639–668.

    Article  Google Scholar 

  • Russell, A. (1970). Cash flows in networks. Management Science, 16(5), 357–373.

    Article  Google Scholar 

  • Seifi, M., & Tavakkoli-Moghaddam, R. (2008). A new bi-objective model for a multi-mode resource-constrained project scheduling problem with discounted cash flows and four payment models. International Journal of Engineering, Transaction A: Basic, 21(4), 347–360.

    Google Scholar 

  • Sprecher, A. (2000). Scheduling resource-constrained projects competitively at modest memory requirements. Management Science, 46(5), 710–723.

    Article  Google Scholar 

  • Sung, C., & Lim, S. (1994). A project activity scheduling problem with net present value measure. International Journal of Production Economics, 37(2), 177–187.

    Article  Google Scholar 

  • Talbot, F. B. (1982). Resource-constrained project scheduling with time-resource tradeoffs: The nonpreemptive case. Management Science, 28(10), 1197–1210.

    Article  Google Scholar 

  • Ulusoy, G., Sivrikaya-Şerifoğlu, F., & Şahin, Ş. (2001). Four payment models for the multi-mode resource constrained project scheduling problem with discounted cash flows. Annals of Operations Research, 102(1–4), 237–261.

    Article  Google Scholar 

  • Van de Vonder, S., Demeulemeester, E., Herroelen, W., & Leus, R. (2005). The use of buffers in project management: The trade-off between stability and makespan. International Journal of Production Economics, 97(2), 227–240.

    Article  Google Scholar 

  • Van de Vonder, S., Demeulemeester, E., Herroelen, W., & Leus, R. (2006). The trade-off between stability and makespan in resource-constrained project scheduling. International Journal of Production Research, 44(2), 215–236.

    Article  Google Scholar 

  • 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 Research, 201(2), 409–418.

    Article  Google Scholar 

  • Vanhoucke, M., & Debels, D. (2008). The impact of various activity assumptions on the lead time and resource utilization of resource-constrained projects. Computers & Industrial Engineering, 54(1), 140–154.

    Article  Google Scholar 

  • Węglarz, J., Józefowska, J., Mika, M., & Waligóra, G. (2011). Project scheduling with finite or infinite number of activity processing modes: A survey. European Journal of Operational Research, 208(3), 177–205.

    Article  Google Scholar 

  • Yan, L., Jinsong, B., Xiaofeng, H., & Ye, J. (2009). A heuristic project scheduling approach for quick response to maritime disaster rescue. International Journal of Project Management, 27(6), 620–628.

    Article  Google Scholar 

  • Yu, L., Wang, S., Wen, F., & Lai, K. K. (2012). Genetic algorithm-based multi-criteria project portfolio selection. Annals of Operations Research, 197(1), 71–86.

    Article  Google Scholar 

  • Zhou, M., & Askin, R. G. (1998). Formation of general GT cells: An operation-based approach. Computers & Industrial Engineering, 34(1), 147–157.

    Article  Google Scholar 

  • Zhu, D., & Padman, R. (1999). A metaheuristic scheduling procedure for resource-constrained projects with cash flows. Naval Research Logistics (NRL), 46(8), 912–927.

    Article  Google Scholar 

Download references

Acknowledgments

The authors would like to thank Dr. Mohammad Gholami (Post-doctoral fellow; University of Calgary-Abb.CA) for his positive comments during the writing of this manuscript. We also want to sincerely thank the editor and anonymous reviewers for their invaluable comments.

Author information

Authors and Affiliations

  1. Department of Mechanical and Manufacturing Engineering, University Putra Malaysia (UPM), 43400, Kuala Lumpur, Malaysia

    Aidin Delgoshaei & Mohd Khairol Anuar Ariffin

  2. Department of Civil Engineering, Institute for Structural Mechanics, Bauhaus-Universität Weimar, Weimar, Germany

    Timon Rabczuk

  3. Department of Mechanical Engineering, College of Engineering, Lawrence Technological University, 21000 W 10 Mile Rd., Southfield, MI, 48075, USA

    Ahad Ali

Authors
  1. Aidin Delgoshaei
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Timon Rabczuk
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ahad Ali
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mohd Khairol Anuar Ariffin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Aidin Delgoshaei.

Appendix

Appendix

Precedence matrix for experiments number 1 and 2 in Table 3.

figure a

Precedence matrix for experiments number 3 and 4 in Table 3.

figure b

Precedence matrix for experiments number 5 and 6 in Table 3.

figure c

Precedence matrix for experiments number 7 and 8 in Table 3.

figure d

Precedence matrix for experiments number 9 and 10 in Table 3.

figure e

Precedence matrix for experiments number 11 and 12 in Table 3.

figure f

Precedence matrix for experiments number 13 and 14 in Table 3.

figure g

Precedence matrix for experiments number 15 and 16 in Table 3.

figure h

Precedence matrix for experiments number 17 and 18 in Table 3.

figure i

Precedence matrix for experiments number 19 and 20 in Table 3.

figure j

In order to receive precedence matrices for experiments with 100, 200, 500 and 1000 activities, please send an email to the corresponding author.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Delgoshaei, A., Rabczuk, T., Ali, A. et al. An applicable method for modifying over-allocated multi-mode resource constraint schedules in the presence of preemptive resources. Ann Oper Res 259, 85–117 (2017). https://doi.org/10.1007/s10479-016-2336-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-016-2336-8

Keywords

Search

Navigation