International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12

line decor
  
line decor

 Volume 13, Issue 9 (September 2026), Pages: 156-167

----------------------------------------------

 Original Research Paper

Optimizing solid waste management using a GIS-based smart decision framework: A case study of Khartoum State, Sudan

 Author(s): 

Ahmed Abdelrhman 1, *, Mohamed A. Damos 2, Abdolraheem Khader 3, 4, Mohammed Ameen 5, Areej Althubaity 6, Mubarak Himmat 7, Ali Ahmed 8, Ahmed Hamza Osman 5

 Affiliation(s):

1Department of Surveying Engineering, College of Graduate Studies, Karary University, Khartoum, Sudan
2Department of Surveying Engineering, College of Engineering, Karary University, Khartoum, Sudan
3School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China
4Software Engineering Department, Faculty of Computer Science and Information Technology, Karary University, Khartoum, Sudan
5Department of Information Systems, Faculty of Computing and Information Technology in Rabigh, King Abdulaziz University, Jeddah 21589, Saudi Arabia
6Cybersecurity Department, College of Computing, Umm Al-Qura University, Makkah, Saudi Arabia
7Faculty of Engineering and Computing, Liwa University, Abu Dhabi, United Arab Emirates
8Department of Computer Science, Faculty of Computing and Information Technology in Rabigh, King Abdulaziz University, Jeddah 21589, Saudi Arabia

 Full text

    Full Text - PDF

 * Corresponding Author. 

   Corresponding author's ORCID profile:  https://orcid.org/0009-0005-2011-2258

 Digital Object Identifier (DOI)

 
https://doi.org/10.21833/ijaas.2026.09.015

 Abstract

Accelerating urbanization in Khartoum State has placed considerable pressure on solid waste management (SWM) infrastructure. Inadequate landfill site selection and inefficient collection planning have created environmental risks, economic inefficiency, and public health concerns. This study proposes an integrated GIS-based decision-support framework combining Multi-Criteria Decision Analysis (MCDA) and the Analytic Hierarchy Process (AHP) to improve waste management in Khartoum, Omdurman, and Khartoum North. Seven spatial criteria were weighted using AHP and integrated in ArcGIS to produce a three-class suitability map. Location-Allocation analysis identified three suitable sites, confirming the suitability of the existing Khartoum North site and designating the other two as transfer stations. Service Area Analysis assessed accessibility, while container locations and capacities were optimized according to household walking distances (maximum 250 m) and building density. Python simulations compared two collection scenarios for February 2026: a fixed daily schedule and a demand-driven schedule triggered when containers reached 80% capacity. The demand-driven approach reduced total travel distance by 19.4%, working hours by 44%, and operational costs by 19%. The proposed framework provides a transparent, reproducible, and cost-effective approach to urban solid waste management, particularly in resource-constrained settings.

 © 2026 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

Geographic information systems, Multi-criteria decision analysis, Analytic hierarchy process, Solid waste management, Smart waste collection

 Article history

Received 25 May 2026, Received in revised form 21 September 2026, Accepted 26 September 2026

 Acknowledgment

The authors gratefully acknowledge the Deanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah, Saudi Arabia, for funding this project under grant No. (IPP: 22-830-2026) and for providing technical support. 

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

Abdelrhman A, Damos MA, Khader A, Ameen M, Althubaity A, Himmat M, Ahmed A, and Osman AH (2026). Optimizing solid waste management using a GIS-based smart decision framework: A case study of Khartoum State, Sudan. International Journal of Advanced and Applied Sciences, 13(9): 156-167

  Permanent Link to this page

---------------------------------------------- 

 References (21)

  1. Abdallah M, Talib MA, Feroz S, Nasir Q, Abdalla H, and Mahfood B (2020). Artificial intelligence applications in solid waste management: A systematic research review. Waste Management, 109: 231-246. https://doi.org/10.1016/j.wasman.2020.04.057   [Google Scholar] PMid:32428727
  2. Akhtar M, Hannan MA, Begum RA, Basri H, and Scavino E (2017). Backtracking search algorithm in CVRP models for efficient solid waste collection and route optimization. Waste Management, 61: 117-128. https://doi.org/10.1016/j.wasman.2017.01.022   [Google Scholar] PMid:28153405
  3. Aleyadeh S and Taha AEM (2018). An IoT-based architecture for waste management. In the 2018 IEEE International Conference on Communications Workshops (ICC Workshops), IEEE, Kansas City, USA: 1-4. https://doi.org/10.1109/ICCW.2018.8403750   [Google Scholar]
  4. Al-Hanbali A, Alsaaideh B, and Kondoh A (2011). Using GIS-based weighted linear combination analysis and remote sensing techniques to select optimum solid waste disposal sites within Mafraq City, Jordan. Journal of Geographic Information System, 3(4): 267-278. https://doi.org/10.4236/jgis.2011.34023   [Google Scholar]
  5. Bányai T, Tamás P, Illés B, Stankevičiūtė Ž, and Bányai Á (2019). Optimization of municipal waste collection routing: Impact of industry 4.0 technologies on environmental awareness and sustainability. International Journal of Environmental Research and Public Health, 16(4): 634. https://doi.org/10.3390/ijerph16040634   [Google Scholar] PMid:30795548 PMCid:PMC6406842
  6. Catania V and Ventura D (2014). An approach for monitoring and smart planning of urban solid waste management using smart-M3 platform. In the Proceedings of 15th Conference of Open Innovations Association FRUCT, IEEE, St. Petersburg, Russia: 24-31. https://doi.org/10.1109/FRUCT.2014.6872422   [Google Scholar]
  7. Demesouka OE, Vavatsikos AP, and Anagnostopoulos KP (2013). Suitability analysis for siting MSW landfills and its multicriteria spatial decision support system: Method, implementation and case study. Waste Management, 33(5): 1190-1206. https://doi.org/10.1016/j.wasman.2013.01.030   [Google Scholar] PMid:23453354
  8. Faccio M, Persona A, and Zanin G (2011). Waste collection multi objective model with real time traceability data. Waste Management, 31(12): 2391-2405. https://doi.org/10.1016/j.wasman.2011.07.005   [Google Scholar] PMid:21821406
  9. Gbanie SP, Tengbe PB, Momoh JS, Medo J, and Kabba VTS (2013). Modelling landfill location using geographic information systems (GIS) and multi-criteria decision analysis (MCDA): Case study Bo, Southern Sierra Leone. Applied Geography, 36: 3-12. https://doi.org/10.1016/j.apgeog.2012.06.013   [Google Scholar]
  10. Ghiani G, Laganà D, Manni E, Musmanno R, and Vigo D (2014). Operations research in solid waste management: A survey of strategic and tactical issues. Computers & Operations Research, 44: 22-32. https://doi.org/10.1016/j.cor.2013.10.006   [Google Scholar]
  11. Ghose MK, Dikshit AK, and Sharma SK (2006). A GIS based transportation model for solid waste disposal–A case study on Asansol municipality. Waste Management, 26(11): 1287-1293. https://doi.org/10.1016/j.wasman.2005.09.022   [Google Scholar] PMid:16377168
  12. Guerrero LA, Maas G, and Hogland W (2013). Solid waste management challenges for cities in developing countries. Waste Management, 33(1): 220-232. https://doi.org/10.1016/j.wasman.2012.09.008   [Google Scholar] PMid:23098815
  13. Han H and Ponce Cueto E (2015). Waste collection vehicle routing problem: Literature review. Promet - Traffic&Transportation, 27(4): 345-358. https://doi.org/10.7307/ptt.v27i4.1616   [Google Scholar]
  14. Hannan MA, Arebey M, Begum RA, and Basri H (2011). Radio frequency identification (RFID) and communication technologies for solid waste bin and truck monitoring system. Waste Management, 31(12): 2406-2413. https://doi.org/10.1016/j.wasman.2011.07.022   [Google Scholar] PMid:21871788
  15. Hemmelmayr VC, Doerner KF, Hartl RF, and Vigo D (2014). Models and algorithms for the integrated planning of bin allocation and vehicle routing in solid waste management. Transportation Science, 48(1): 103-120. https://doi.org/10.1287/trsc.2013.0459   [Google Scholar]
  16. Kang YO, Yabar H, Mizunoya T, and Higano Y (2024). Optimal landfill site selection using ArcGIS multi-criteria decision-making (MCDM) and analytic hierarchy process (AHP) for Kinshasa city. Environmental Challenges, 14: 100826. https://doi.org/10.1016/j.envc.2023.100826   [Google Scholar]
  17. Karadimas NV, Kouzas G, Anagnostopoulos I, and Loumos V (2005). Urban solid waste collection and routing: The ant colony strategic approach. International Journal of Simulation: Systems, Science & Technology, 6(12-13): 45-53.   [Google Scholar]
  18. Kaza S, Yao LC, Bhada-Tata P, and Van Woerden F (2018). What a waste 2.0: A global snapshot of solid waste management to 2050. World Bank, Washington, DC, USA. https://doi.org/10.1596/978-1-4648-1329-0   [Google Scholar]
  19. Saaty TL (1980). The analytic hierarchy process: Planning, priority setting, resource allocation. McGraw-Hill International Book Company, New York, USA.   [Google Scholar]
  20. Şener Ş, Şener E, Nas B, and Karagüzel R (2010). Combining AHP with GIS for landfill site selection: A case study in the Lake Beyşehir catchment area (Konya, Turkey). Waste Management, 30(11): 2037-2046. https://doi.org/10.1016/j.wasman.2010.05.024   [Google Scholar] PMid:20594819
  21. Vu HL, Ng KTW, and Bolingbroke D (2019). Time-lagged effects of weekly climatic and socio-economic factors on ANN municipal yard waste prediction models. Waste Management, 84: 129-140. https://doi.org/10.1016/j.wasman.2018.11.038   [Google Scholar] PMid:30691884