Multi-Goal Programming Model for Optimal Priority in Building Material Production Planning
DOI:
https://doi.org/10.25077/jmua.15.3.371-387.2026Keywords:
Goal priority, Multi-goal programming, Objective function, Production planning, ProfitAbstract
One crucial activity for a company’s long-term sustainability is establishing an effective production planning policy. Currently, CV Lembah Melintang relies on consumer demand to determine its production process, which often leads to suboptimal resource utilization. This research aims to develop an optimal production plan using a Multi-Goal Programming (MGP) model to maximize resource use and increase company income.
The MGP model, an extension of the goal programming method, allows for multiple objectives by incorporating deviation variables to handle conflicts between goals. In this study, the objectives are: maximizing total production, minimizing production costs, and maximizing profit, subject to relevant resource constraints. Data analysis and computation were carried out using POM-QM v5 software.
The results indicate that the production plan successfully met the company’s targets: sales volume was achieved, production costs remained below the target limit of IDR 922,105,662.4, and profit reached the target of IDR 564,080,764 for the 2023 period. The study concludes that the MGP model is an effective decision-support tool for improving production planning policies and aligning multiple strategic goals in manufacturing environments.
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References
[1] A. Bueno, M. Godinho Filho, and A. G. Frank, “Smart production planning and control in the Industry 4.0 context: A systematic literature review,” Computers & Industrial Engineering, vol. 149, p. 106774, 2020, doi:
10.1016/j.cie.2020.106774.
[2] J. Lohmer and R. Lasch, “Production planning and scheduling in multifactory production networks: a systematic literature review,” International
Journal of Production Research, vol. 59, no. 7, pp. 2028–2054, 2021, doi:
10.1080/00207543.2020.1797207.
[3] J. P. Herrmann, S. Tackenberg, E. Padoano, and T. Gamber, “Approaches of
Production Planning and Control under Industry 4.0: A Literature Review,”
Journal of Industrial Engineering and Management, vol. 15, no. 1, pp. 4–30,
2022, doi: 10.3926/jiem.3582.
[4] J. P. Usuga Cadavid, S. Lamouri, B. Grabot, R. Pellerin, and A. Fortin, “Machine learning applied in production planning and control: a state-of-the-art in
the era of industry 4.0,” Journal of Intelligent Manufacturing, vol. 31, no. 6,
pp. 1531–1558, 2020, doi: 10.1007/s10845-019-01531-7.
[5] F. Angizeh, H. Montero, A. Vedpathak, and M. Parvania, “Optimal production scheduling for smart manufacturers with application to food production
planning,” Computers & Electrical Engineering, vol. 84, p. 106609, 2020, doi:
10.1016/j.compeleceng.2020.106609.
[6] D. Izci, S. Ekinci, S. Orenc, and A. Demiroren, “Improved Artificial Electric
Field Algorithm Using Nelder-Mead Simplex Method for Optimization Problems,” in Proceedings of the 4th International Symposium on Multidisciplinary
Studies and Innovative Technologies (ISMSIT), 2020, pp. 0–4, doi: 10.1109/ISMSIT50672.2020.9255255.
[7] F. Firmansyah, D. J. Panjaitan, M. Salayan, and A. D. Silalahi, “Optimization
of Production Costs With Simplex Method,” Journal of Community Research
and Service, vol. 4, no. 2, p. 66, 2020, doi: 10.24114/jcrs.v4i2.15277.
[8] Y. Lee, A. Resiga, S. Yi, and C. Wern, “The Optimization of Machining Parameters for Milling Operations by Using the Nelder-Mead Simplex Method,”
Journal of Manufacturing and Materials Processing, vol. 4, no. 3, pp. 1–22, 2020,
doi: 10.3390/jmmp4030066.
[9] M. B. Uddin, M. A. H. Khan, and M. S. Islam, “Application of Linear Programming Techniques in Agriculture,” International Journal of Scientific Research and Publications, vol. 13, no. 5, pp. 122–128, 2023, doi:
10.29322/ijsrp.13.05.2023.p13715.
[10] R. Jayaraman, C. Colapinto, D. Liuzzi, and D. La Torre, “Planning sustainable
development through a scenario-based stochastic goal programming model,”
Operations Research, vol. 17, no. 3, pp. 789–805, 2017, doi: 10.1007/s12351-016-
0239-8.
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