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Determining Control Points in the Project Life Cycle: A Heuristic Approach Utilizing Tabu Search | ||
| Control and Optimization in Applied Mathematics | ||
| مقاله 10، دوره 10، شماره 1 - شماره پیاپی 19، شهریور 2025، صفحه 163-173 اصل مقاله (440.08 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.30473/coam.2025.73812.1290 | ||
| نویسنده | ||
| Narjes Sabeghi | ||
| Department of Mathematics, Faculty of Basic Sciences, Velayat University, Iranshahr, Iran. | ||
| چکیده | ||
| A critical aspect of successful project management is ensuring that execution aligns with the baseline schedule. However, traditional project control methods often struggle to effectively address the uncertainties and deviations that can arise during project execution, leading to delays and inefficiencies. To tackle these challenges, this paper introduces a novel heuristic approach based on the Tabu Search (TS) algorithm for identifying discrete control points throughout the project life cycle. These control points enable proactive monitoring, timely deviation detection, and corrective actions, significantly minimizing project delays. Unlike traditional scheduling techniques, which can be rigid and reactive, our proposed method dynamically adjusts control points to enhance project oversight. Experimental results on benchmark instances from the Kolisch library demonstrate that our approach significantly reduces project delays, with up to 20% improvements compared to initial schedules in certain scenarios. These findings underscore the effectiveness of the TS algorithm in enhancing project control strategies, highlighting its potential applicability in real-world project management scenarios. | ||
تازه های تحقیق | ||
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| کلیدواژه‌ها | ||
| Project management؛ Scheduling؛ Proactive management؛ Control points؛ Tabu search algorithm | ||
| مراجع | ||
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[1] de Soto, B.G., Rosarius, A., Rieger, J., Chen, Q., Adey, B.T. (2017). “Using a tabu-search algorithm and 4D models to improve construction project schedules”, Procedia Engineering, 196, 698-705, doi:10.1016/j.proeng.2017.07.236.
[2] Kolisch, R., Sprecher, A. (1997). “PSPLIB-a project scheduling problem library: OR software-ORSEP operations research software exchange program”, European Journal of Operational Research, 96(1), 205-216, doi:10.1016/S0377-2217(96)00170-1.
[3] Pan, N.H., Hsaio, P.W., Chen, K.Y. (2008). “A study of project scheduling optimization using tabu search algorithm”, Engineering Applications of Artificial Intelligence, 21(7), 1101-1112, doi: 10.1016/j.engappai.2007.11.006.
[4] Pellerin, R., Perrier, N. (2019). “A review of methods, techniques and tools for project planning and control”, International Journal of Production Research, 57(7), 2160-2178, doi: 10.1080/ 00207543.2018.1524168.
[5] Sabeghi, N., Tareghian, H.R. (2020). “Using the generalized maximum covering location model to control a project’s progress”, Computational Management Science, 17(1), 1-21, doi:10.1007/s10287-018-0301-5.
[6] Sabeghi, N., Tareghian, H.R., Demeulemeester, E., Taheri, H. (2015). “Determining the timing of project control points using a facility location model and simulation”, Computers & Operations Research, 61, 69-80, doi:10.1016/j.cor.2015.03.006.
[7] Song, J., Martens, A., Vanhoucke, M. (2022). “Using earned value management and schedule risk analysis with resource constraints for project control”, European Journal of Operational Research, 297(2), 451-466, doi:10.1016/j.ejor.2021.05.036.
[8] Thomas, P.R., Salhi, S. (1998). “A tabu search approach for the resource constrained project scheduling problem”, Journal of Heuristics, 4, 123-139, doi:10.1023/A:1009673512884.
[9] Yang, B., Geunes, J., O’Brien, W.J. (2001). “Resource-constrained project scheduling: Past work and new directions”, Department of Industrial and Systems Engineering, University of Florida, Tech. Rep. | ||
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آمار تعداد مشاهده مقاله: 40 تعداد دریافت فایل اصل مقاله: 47 |
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