Ejlaly, Babak, Abbasi, Morteza, Zahedi, Mohammadreza, Yousefi Nejad Attari, Mahdi. (1404). A Systematic Review of Project Scheduling Models under Renewable Resource Constraints and Uncertainty. , 18(2), 150-182. doi: 10.22059/imj.2026.404865.1008269
Babak Ejlaly; Morteza Abbasi; Mohammadreza Zahedi; Mahdi Yousefi Nejad Attari. "A Systematic Review of Project Scheduling Models under Renewable Resource Constraints and Uncertainty". , 18, 2, 1404, 150-182. doi: 10.22059/imj.2026.404865.1008269
Ejlaly, Babak, Abbasi, Morteza, Zahedi, Mohammadreza, Yousefi Nejad Attari, Mahdi. (1404). 'A Systematic Review of Project Scheduling Models under Renewable Resource Constraints and Uncertainty', , 18(2), pp. 150-182. doi: 10.22059/imj.2026.404865.1008269
Ejlaly, Babak, Abbasi, Morteza, Zahedi, Mohammadreza, Yousefi Nejad Attari, Mahdi. A Systematic Review of Project Scheduling Models under Renewable Resource Constraints and Uncertainty. , 1404; 18(2): 150-182. doi: 10.22059/imj.2026.404865.1008269

A Systematic Review of Project Scheduling Models under Renewable Resource Constraints and Uncertainty

Industrial Management Journal
دوره 18، شماره 2، 2026، صفحه 150-182    اصل مقاله (1.74 M)
نوع مقاله: Original Research Article
شناسه دیجیتال (DOI): 10.22059/imj.2026.404865.1008269
نویسندگان
Babak Ejlaly1؛ Morteza Abbasi* 2؛ Mohammadreza Zahedi3؛ Mahdi Yousefi Nejad Attari4
1Ph.D. Candidate in Industrial engineering Technology Management, Faculty of Industries and Management, Malek Ashtar University of Technology, Tehran, Iran.
2Assistant Prof., Faculty of Industries and Management, Malek Ashtar University of Technology, Tehran, Iran.
3Associate Prof, Faculty of Industries and Management, Malek Ashtar University of Technology, Tehran, Iran.
4Associate Prof., Department of Industrial Engineering, Bon.C., Islamic Azad University, Bonab, Iran.
چکیده
Objective: This study aims to develop a comprehensive resource-constrained project scheduling model (RCPSP) that accounts for uncertainty in activity durations and resource availability, thereby addressing the limitations of deterministic approaches.
Methodology: A mathematical formulation of the RCPSP is extended to an uncertain environment (URCPSP), considering renewable and semi-renewable resources under multiple constraints. The proposed framework integrates deterministic and stochastic components to better handle resource conflicts and project disruptions.
Results: Results indicate that classical RCPSP models fail to represent real-world project dynamics. Incorporating uncertainty and mixed resource types enhances scheduling flexibility and solution robustness while minimizing total project duration and resource fluctuation.
Conclusion: The proposed model provides a unified framework for project scheduling under uncertainty, supporting decision-making in complex environments. Future work may extend the model to multi-project contexts and advanced metaheuristic optimization techniques.
کلیدواژه‌ها
Project scheduling؛ resource constraints؛ uncertainty؛ renewable resources؛ optimization algorithm
مراجع
آمار
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