Vol. 8 No. 4 (2020): Business & Management Studies: An International Journal


Dr., Erciyes University, FEAS, Business
Prof. Dr., Erciyes University, FEAS, Business

Published 2020-12-10


  • Proje Çizelgeleme, Dinamik Proje, Reaktif Çizelge, Matematiksel Model
  • Project Scheduling, Dynamic Project, Reactive Schedule, Mathematical Model

How to Cite

RUHLUSARAÇ, M. ., & ÇALIŞKAN, F. (2020). A MATHEMATICAL MODEL FOR DYNAMIC PROJECT SCHEDULING PROBLEM AND REACTIVE SCHEDULING IMPLEMENTATION. Business & Management Studies: An International Journal, 8(4), 83–97. https://doi.org/10.15295/bmij.v8i4.1708


In today's real-life implementations, projects are executed under uncertainty in a dynamic environment. In addition to resource constraints, the baseline schedule is affected due to the unpredictability of the dynamic environment. Uncertainty-based dynamic events experienced during project execution may change the baseline schedule partially or substantially and require projects' rescheduling. In this study, a mixed-integer linear programming model is proposed for the dynamic resource-constrained project scheduling problem. Three dynamic situation scenarios are solved with the proposed model, including machine breakdown, worker sickness, and electricity power cut. Finally, generated reactive schedules are completed later than the baseline schedule.


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  1. Adamu, P. I., Akinwumi, I. I., & Okagbue, H. I. (2019). Reactive project scheduling: minimizing delays in the completion times of projects. Asian Journal of Civil Engineering, 20, 1189-1202.
  2. Ben Issa, S., Patterson, R.A., & Tu, Y. (2020). Solving resource-constrained multiproject environment under different activity assumptions, International Journal of Production Economics, 107936, 1-41.
  3. Çapa, C. (2013). A Three-Phase Approach For Robust Project Scheduling: An Application For R&D Project Scheduling, Master Thesis, Sabanci University, 1-209.
  4. Collyer, S., & Warren, C. M. J. (2009). Project management approaches for dynamic environments. International Journal of Project Management, 27(4), 355–364.
  5. Da Silva, André Renato Villela, & Ochi, L. S. (2010). Hybrid heuristics for dynamic resource-constrained project scheduling problem. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6373 LNCS, 73–87.
  6. Da Silva, Andre Renato Villela, Ochi, L. S., & Santos, H. G. (2008). New effective algorithm for Dynamic Resource Constrained Project Scheduling Problem, (June), 1–5.
  7. Hauder V.A., Beham A., Raggl S., Parragh S.N., & Affenzeller M. (2020) Resource-constrained multi-project scheduling with activity and time flexibility. Computers & Industrial Engineering, 150, 106857, 1-42.
  8. Hazir, O., & Ulusoy, G. (2019). A Classifıcation And Review Of Approaches And Methods For Modeling Uncertainty In Projects. International Journal of Production Economics, 1–52.
  9. Hazır, Ö., Eryılmaz, U., & Hafızoğlu, M. (2014). Proje Yönetimi: Analitik Yaklaşımlar. PMI TR.
  10. Joo, B. J., Chua, T. J., Cai, T. X., & Chua, P. C. (2019). Coordination-based reactive resource-constrained project scheduling. Procedia CIRP, 81, 51–56.
  11. Krajewski, L. J., Ritzman, L. P., & Malhotra, M. K. (2010). Operations Management Processes and Supply Chains, Pearson Prentice Hall, 1-640.
  12. Leusin, M., Frazzon, E., Uriona Maldonado, M., Kück, M., & Freitag, M. (2018). Solving the Job-Shop Scheduling Problem in the Industry 4.0 Era. Technologies, 6(4), 107.
  13. Pritsker, A. Alan B. and Lawrence J. Watters. (1968). A Zero-One Programming Approach to Scheduling with Limited Resources. Santa Monica, CA: RAND Corporation, 1-59.
  14. Ruhlusaraç, M., & Çalışkan, F. (2018). Ağırlıklı Erken ve Geç Bitirme Maliyetli Çok Modlu Kaynak Kısıtlı Çoklu Proje Çizelgeleme Problemi. International Science and Technology Conference, July 18-20, 2018 Paris,France, 60–64.
  15. Sabuncuoglu, I., & Bayiz, M. (2000). Analysis of reactive scheduling problems in a job shop environment. European Journal of Operational Research, 126(3), 567–586.
  16. Song, W., Xi, H., Kang, D., & Zhang, J. (2018). An Agent-based Simulation System for Multi-Project Scheduling under Uncertainty. Simulation Modelling Practice and Theory, 86, 187-203.
  17. Van de Vonder, S. (2006). Proactive-reactive procedures for robust project scheduling. Applied Economics, Doctoral Dissertation, (247), 1-219.
  18. Van de Vonder, S., Ballestín, F., Demeulemeester, E., & Herroelen, W. (2007). Heuristic procedures for reactive project scheduling. Computers and Industrial Engineering, 52(1), 11–28.
  19. Van de Vonder, S., Demeulemeester, E., & Herroelen, W. (2008). Proactive heuristic procedures for robust project scheduling: An experimental analysis. European Journal of Operational Research, 189(3), 723–733.
  20. Van De Vonder, S., Demeulemeester, E., & Herroelen, W. (2007). A classification of predictive-reactive project scheduling procedures. Journal of Scheduling, 10(3), 195–207.
  21. Wang, W., Ge, X., Li, L., & Su, J. (2019). Proactive and Reactive Multi-Project Scheduling in Uncertain Environment. IEEE Access, 7, 88986–88997.