An Optimization Approach Goal Programming to Improve the Academic and Administrative Quality of Postgraduate Programs

Zainal Azis, Al-Khowarizmi Al-Khowarizmi, Tua Halomoan Harahap, Muliawan Firdaus, Irvan Irvan

Abstract


The main objective of this article is to implement the GP approach to improve academic and administrative performance at UMSU postgraduates. In the context of expected results, this article is intended so that UMSU postgraduates can establish strategies to achieve higher academic standards and create a more conducive educational environment through achieving predetermined targets, which include improving the quality of teaching and learning, effectiveness of program administration, and student and lecturer satisfaction with the academic process. The article can make a significant contribution to the academic literature in the field of educational management and operations by offering a new perspective on the application of GP and AHP in a higher education context. Specifically, this article shows how quantitative approaches can be used to improve decision making in the management of academic programs and administration, thereby providing valuable practical and theoretical insights for the development of educational policy and managerial practice in the higher education sector. It can be seen from the results that the parameters in this paper contribute to the weight of the objective (w_1), target (T_1), and the budget constraint (B), all of which play an important role in determining the optimal solution produced by the model

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References


Alyahyan, E., & Düştegör, D. (2020). Predicting academic success in higher education: literature review and best practices. International Journal of Educational Technology in Higher Education, 17(1), 3.

Dagistanli, H. A., & Üstün, Ö. (2023). An integrated Multi-Criteria Decision Making and Multi-Choice Conic Goal Programming approach for customer evaluation and manager assignment. Decision Analytics Journal, 8(March), 100270. https://doi.org/10.1016/j.dajour.2023.100270

El Khatib, M., Al Mulla, A., & Al Ketbi, W. (2022). The role of blockchain in e-governance and decision-making in project and program management. Advances in Internet of Things, 12(3), 88–109.

Ficken, F. A. (2015). The simplex method of linear programming. Courier Dover Publications.

Gaspars-Wieloch, H. (2020). A new application for the Goal Programming—The Target Decision Rule for uncertain problems. Journal of Risk and Financial Management, 13(11), 280.

Gebre, S. L., Cattrysse, D., Alemayehu, E., & Van Orshoven, J. (2021). Multi-criteria decision making methods to address rural land allocation problems: A systematic review. International Soil and Water Conservation Research, 9(4), 490–501.

Guggeri, E. M., Ham, C., Silveyra, P., Rossit, D. A., & Piñeyro, P. (2023). Goal programming and multi-criteria methods in remanufacturing and reverse logistics: Systematic literature review and survey. Computers & Industrial Engineering, 109587.

Jones, D., & Tamiz, M. (2010). Practical goal programming (Vol. 141). Springer.

Kaur, J., Singh, O., Anand, A., & Agarwal, M. (2023). A goal programming approach for agile-based software development resource allocation. Decision Analytics Journal, 6(August 2022), 100146. https://doi.org/10.1016/j.dajour.2022.100146

Khakzad, N. (2023). A goal programming approach to multi-objective optimization of firefighting strategies in the event of domino effects. Reliability Engineering and System Safety, 239(April), 109523. https://doi.org/10.1016/j.ress.2023.109523

Kim, S.-H., Lee, K.-H., & Kang, D.-W. (2020). Analytic hierarchy process modelling of location competitiveness for a regional logistics distribution center serving northeast Asia. Journal of Korea Trade, 24(3), 20–36.

Li, X., Liu, S., & Sun, Y. (2022). A GP-Based Hierarchical Objectives Decision-Making Method for Building Energy Efficiency Optimization. Buildings, 12(1), 52.

Meidute-Kavaliauskiene, I., Davidaviciene, V., Ghorbani, S., & Sahebi, I. G. (2021). Optimal allocation of gas resources to different consumption sectors using multi-objective goal programming. Sustainability, 13(10), 5663.

Omair, M., Noor, S., Tayyab, M., Maqsood, S., Ahmed, W., Sarkar, B., & Habib, M. S. (2021). The selection of the sustainable suppliers by the development of a decision support framework based on analytical hierarchical process and fuzzy inference system. International Journal of Fuzzy Systems, 23(7), 1986–2003.

Ordu, M., Demir, E., Tofallis, C., & Gunal, M. M. (2021). A novel healthcare resource allocation decision support tool: A forecasting-simulation-optimization approach. Journal of the Operational Research Society, 72(3), 485–500.

Pereira, J. L. J., Oliver, G. A., Francisco, M. B., Cunha Jr, S. S., & Gomes, G. F. (2022). A review of multi-objective optimization: methods and algorithms in mechanical engineering problems. Archives of Computational Methods in Engineering, 29(4), 2285–2308.

Putri, A. N., Hariadi, M., & Rachmadi, R. F. (2024). Multi-objective optimization of production: A case study on simplex, goal programming, and pareto front models. Journal of Optimization in Industrial Engineering, 16(2), 63–73.

Rehman, A. U., Usmani, Y. S., Mian, S. H., Abidi, M. H., & Alkhalefah, H. (2023). Simulation and Goal Programming Approach to Improve Public Hospital Emergency Department Resource Allocation. Systems, 11(9), 467.

Ryńca, R., & Ziaeian, Y. (2021). Applying the goal programming in the management of the 7P marketing mix model at universities-case study. PloS One, 16(11), e0260067.

Saaty, T. L., & Ozdemir, M. S. (2021). The Encyclicon-Volume 1: A dictionary of decisions with dependence and feedback based on the analytic network process. RWS Publications.

Shamloo, N., Bakhtavar, E., Hewage, K., & Sadiq, R. (2021). Optimization of hydraulic fracturing wastewater management alternatives: A hybrid multi-objective linear programming model. Journal of Cleaner Production, 286, 124950.

Shavazipour, B., & Stewart, T. J. (2021). Multi-objective optimisation under deep uncertainty. Operational Research, 21(4), 2459–2487.

Treiber, M. A., & Treiber, M. A. (2013). Linear Programming and the Simplex Method. Optimization for Computer Vision: An Introduction to Core Concepts and Methods, 67–85.

Uddin, M. S., Miah, M., Khan, M. A.-A., & AlArjani, A. (2021). Goal programming tactic for uncertain multi-objective transportation problem using fuzzy linear membership function. Alexandria Engineering Journal, 60(2), 2525–2533.

Wang, X., Zhao, T., & Chang, C.-T. (2021). An integrated FAHP-MCGP approach to project selection and resource allocation in risk-based internal audit planning: A case study. Computers & Industrial Engineering, 152, 107012.

Wibawa, A. P., Fauzi, J. A., Isbiyantoro, S., Irsyada, R., & Hernández, L. (2019). VIKOR multi-criteria decision making with AHP reliable weighting for article acceptance recommendation. International Journal of Advances in Intelligent Informatics, 5(2).

Zandkarimkhani, S., Mina, H., Biuki, M., & Govindan, K. (2020). A chance constrained fuzzy goal programming approach for perishable pharmaceutical supply chain network design. Annals of Operations Research, 295, 425–452.




DOI: https://doi.org/10.30596/ijems.v7i1.28873

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