Optimizing Provisional Urban Waste Cooking Oil Collection: A Literature Review of MCDM and Set Covering Models
DOI:
https://doi.org/10.24191/a3rwxv13Keywords:
Waste Cooking Oil Management, Multi-Criteria Decision Making, Set Covering ModelAbstract
As urban populations grow, the amount of waste cooking oil (WCO) generated by households also increases. This WCO creates more environmental pollution if not handled properly. Small and Medium Enterprises (SMEs) are responsible for collecting WCO from households but face difficulties due to limited support and poorly planned collection systems. This study focuses on the optimal placement of provisional WCO collection points in urban areas. It uses a two-stage decision-making framework which are combining Multi-Criteria Decision Making (MCDM) and the Set Covering Model (SCM). A systematic literature review is conducted to evaluate the use of MCDM and SCM for WCO collection and facility location planning. However, the review finds no existing research combine MCDM and SCM for WCO collection from households. This represents a critical research gap, especially for planning provisional facilities in dynamic urban settings. To address this, the study proposes a future research direction that uses a two-stage decision-making framework to support better decision-making and improve operational efficiency in urban WCO collection systems.
Downloads
References
Aidoo, E., Nandakumar, C. D., Mwinkume, G., & Raj, A. B. (2025). Leveraging mathematical methods for environmentally friendly waste management: Locating optimal facility sites. Edelweiss Applied Science and Technology, 9(3), 2367–2401. https://doi.org/10.55214/25768484.v9i3.5811
Aljohani, K. (2023). Optimizing the distribution network of a bakery facility: A reduced travelled distance and food-waste minimization perspective. Sustainability, 15(4), 3654. https://doi.org/10.3390/su15043654
Alwi, Habsah, Suzihaque, M. U. H., Kalthum Ibrahim, U., Abdullah, S., & Haron, N. (2022). Biodiesel production from waste cooking oil: A brief review. Materials Today: Proceedings, 63, S490–S495. https://doi.org/10.1016/j.matpr.2022.04.527
Anna, Xirogiannopoulou, & Athanasiou, V. (2025). Collection of household used cooking oil in urban areas of Greece: Opinions and practices of local inhabitants. Environmental Research Communications, 7(2), 025013. https://doi.org/10.1088/2515-7620/adb1a4
Boyacı, Aslı Çalış, Şişman, A., & Sarıcaoğlu, K. (2021). Site selection for waste vegetable oil and waste battery collection boxes: A GIS-based hybrid hesitant fuzzy decision-making approach. Environmental Science and Pollution Research, 28(14), 17431–17444. https://doi.org/10.1007/s11356-020-12080-5
Claudia, F., Bernal Angie, Leon Paul, Gelves Oscar, & Malagon-Romero Dionisio H. (2022). Optimization of a Route for Collecting Waste Cooking Oil in Bogota. Chemical Engineering Transactions, 91, 625–630. https://doi.org/10.3303/CET2291105
Foo, W. H., Koay, S. S. N., Tang, D. Y. Y., Chia, W. Y., Chew, K. W., & Show, P. L. (2022). Safety control of waste cooking oil: Transforming hazard into multifarious products with available pre-treatment processes. Food Materials Research, 2(1), 1–11. https://doi.org/10.48130/FMR-2022-0001
Geng, N., Fu, Q., & Sun, Y. (2021). Stochastic programming of sustainable waste cooking oil for biodiesel supply chain under uncertainty. Journal of Advanced Transportation, 2021(1), 5335625. https://doi.org/10.1155/2021/5335625
Gultekin, C., Olmez, O. B., Balcik, B., Ekici, A., & Ozener, O. O. (2020). A decomposition-based heuristic for a waste cooking oil collection problem. In H. Derbel, B. Jarboui, & P. Siarry (Eds.), Green Transportation and New Advances in Vehicle Routing Problems (pp. 159–176). Springer International Publishing. https://doi.org/10.1007/978-3-030-45312-1_6
Hajduk, S. (2021). Multi-criteria analysis in the decision-making approach for the linear ordering of urban transport based on TOPSIS technique. Energies, 15(1), 274. https://doi.org/10.3390/en15010274
Julia, E., Ramadhani, D. A., & Hasbiyati, I. (2024). Use of the discrete facility location model in optimizing the number and location of fire stations: A case study. Journal of Mathematical Sciences and Optimization, 2(1), 104–114. https://doi.org/10.31258/jomso.v2i1.28
Miç, Pinar, & Antmen, Z. F. (2021). A decision-making model based on TOPSIS, WASPAS, and MULTIMOORA methods for university location selection problem. Sage Open, 11(3), 21582440211040115. https://doi.org/10.1177/21582440211040115
Musa, A. I. (2025). Optimal Location Selection for a New Processing Plant using Supply Chain and Distribution Network Analysis. 11(1). http://dx.doi.org/10.62870/jiss.v11i1.31534
Özder, E. H. (2025). A sustainable multi-criteria decision-making framework for online grocery distribution hub location selection. Processes, 13(6), 1653. https://doi.org/10.3390/pr13061653
Quintana, L., Herrera-Mena, Y., Martínez-Flores, J.-L., Coronado, M., Montero, G., & Cano-Olivos, P. (2020). Design of waste vegetable oil collection networks applying vehicle routing problem and simultaneous pickup and delivery. Acta Logistica, 7(4), 261–268. https://doi.org/10.22306/al.v7i4.188
Rahman, Tawfikur, Deb, N., Alam, M. Z., Moniruzzaman, M., Miah, M. S., Horaira, M. A., & Kamal, R. (2024). Navigating the contemporary landscape of food waste management in developing countries: A comprehensive overview and prospective analysis. Heliyon, 10(12), e33218. https://doi.org/10.1016/j.heliyon.2024.e33218
Rosni, M. Z., Ishak, M. I., Zawawi, A. S. M., & Zaharudin, Z. A. (2022). Location-allocation model of recycling facilities – A case study of Seremban, Malaysia. 1(1). http://dx.doi.org/10.6007/IJAREMS/v11-i1/12119
Shaikh, S. A., Memon, M., & Kim, K.-S. (2021). A multi-criteria decision-making approach for ideal business location identification. Applied Sciences, 11(11), 4983. https://doi.org/10.3390/app11114983
Tarigan, I. M., Muhammad Ade Kurnia Harahap, Endang Setyawati, Jimmy Moedjahedy, Ernie C Avila, & Rahim, R. (2023). A multi-criteria decision-making approach for warehouse location selection using TOPSIS. JINAV: Journal of Information and Visualization, 4(1), 45–52. https://doi.org/10.35877/454RI.jinav1616
Yanık, O. (2024). Multi-criteria decision-making approach in single facility location selection: A Proposal for an integrated model. Kafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 15(29), 129–162. https://doi.org/10.36543/kauiibfd.2024.006
Zaharudin, Z. A., Shuib, A., Hadianti, R., & Rodzi, Z. M. (2023). Towards sustainable city: A covering model for recycling facility location-allocation in Nilai, Malaysia. Science and Technology Indonesia, 8(4), 570–578. https://doi.org/10.26554/sti.2023.8.4.570-578
Zaman, M. M. K., Rodzi, Z., Andu, Y., Shafie, N. A., Sanusi, Z. M., Ghazali, A. W., & Mahyideen, J. M. (2025). Adaptive Utility Ranking Algorithm (AURA): A novel dynamic MCDM method for economic decision-making. International Journal of Economic Sciences, 14(1). https://doi.org/10.31181/ijes1412025182
Zandi, Iman, & Lotfata, A. (2025). Evaluating solar power plant sites using integrated GIS and MCDM methods: A case study in Kermanshah Province. Scientific Reports, 15(1), 3288. https://doi.org/10.1038/s41598-025-87476-9
Zulkifli, A. R., Nurfarhana Ab Wahid, & Salwa Nur Ain Suhaili. (2023). Waste Cooking Oil (WCO) Collection Center Location in Seremban 3 by using AHP. https://ir.uitm.edu.my/id/eprint/83459
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Nurul Falah Mohd Razali, Zati Aqmar Zaharudin, Zahari Md Rodzi (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.