an official journal of: published by:
Editor in Chief: RAFFAELLO COSSU


  • Alhassan Sulemana - Department of Environmental Science, Kwame Nkrumah University of Science and Technology, Ghana
  • Emmanuel Amponsah Donkor - Department of Civil Engineering, Kwame Nkrumah University of Science and Technology, Ghana
  • Eric Kwabena Forkuo - Department of Geomatic Engineering, Kwame Nkrumah University of Science and Technology, Ghana
  • Juliet Asantewaa - Department of Environmental Science, Kwame Nkrumah University of Science and Technology, Ghana
  • Isabella N. A. Ankrah - Department of Environmental Science, Kwame Nkrumah University of Science and Technology, Ghana
  • Abdul Muhaymin O. Musah - Department of Environmental Science, Kwame Nkrumah University of Science and Technology, Ghana

DOI 10.31025/2611-4135/2020.13896

Released under CC BY-NC-ND

Copyright: © 2019 CISA Publisher

Editorial History

  • Received: 16 Jul 2019
  • Revised: 31 Oct 2019
  • Accepted: 08 Nov 2019
  • Available online: 28 Jan 2020


Solid waste collection constitutes 60-80% of the total solid waste management cost. Reduction of solid waste collection cost can be achieved through route optimization in a geographic information system (GIS) environment. The purpose of this study was to generate optimized routes for solid waste collection on Kwame Nkrumah University of Science and Technology campus in Kumasi, Ghana. The study modelled the existing routes for a complete collection cycle using travel time criteria and generated optimized routes for same using an ArcGIS software. Validation of the optimized outcome (travel distance and travel time) was done by subjecting the solid waste collection trucks to the optimized routes. The results from the study showed significant reduction in total travel time from 1,000.75 mins to 855.70 mins for existing and optimized routes respectively, translating into saving of 14.5%. Total travel distance significantly reduced from 367.30 km to 334.20 km for existing and optimized routes respectively, representing saving of 9.0%. Significant savings in travel time and travel distance have implications on reduction of fuel and maintenance cost of institutional solid waste collection trucks. The results indicate that the application of GIS-based route optimization in solid waste collection can provide significant improvement in reduction of operating cost.



Addo, I. B., Adei, D., and Acheampong, E. O. (2015). Solid Waste Management and Its Health Implications on the Dwellers of Kumasi Metropolis, Ghana. Current Research Journal of Social Sciences, 7(3), 81-93

Ansari, M., and Pakrou, S. (2015). Optimization of MSW collection routes using GIS (case study : Tabriz City). Current World Environment, 10(1), 882–890.
DOI 10.12944/CWE.10.Special-Issue1.107

Apaydin, O., and Gonullu, M. T. (2007). Route optimization for solid waste collection: Trabzon (Turkey) case study. Global NEST Journal, 9(1), 6-11

Beliën, J., De Boeck, L., and Van Ackere, J. (2014). Municipal solid waste collection and management problems: A literature review. Transportation Science, 48(1), 78–102.
DOI 10.1287/trsc.1120.0448

Chalkias, C., and Lasaridi, K. (2009). A GIS based model for the optimisation of municipal solid waste collection : the case study of Nikea , Athens , Greece. WSEAS Transactions on Environment and Development, 5(10), 640–650

Chalkias, C., and Lasaridi, K. (2009). Optimizing municipal solid waste collection using GIS. 5th International Conference on Energy, Environment, Ecosystems and Sustainable Development/2nd International Conference on Landscape Architecture, Greece. In: Proceedings of Energy, Environment, Ecosystems, Development and, Landscape Architecture, 45–50

Coffey, M., and Coad, A. (2010). Collection of municipal solid waste in developing countries. UN-HABITAT, Malta

Diaz, L. F., Savage, G. M., and Eggerth, L. L. (2005). Solid Waste Management. (L. L. Eggerth, G. M. Savage, and L. F. Diaz, Eds.), Cities (Vol. 1).
DOI 10.1002/9780470999677

Kinobe, J. R., Bosona, T., Gebresenbet, G., Niwagaba, C. B., and Vinner˚as, B. (2015). Optimization of waste collection and disposal in Kampala city. Habitat International, 49, 126–137

Li, C.-Z., Zhang, Y., Liu, Z.-H., Meng, X., and Du, J. (2014). Optimization of MSW collection routing system to reduce fuel consumption and pollutant emissions. Nature Environment and Pollution Technology, 13(1), 177–184

Malakahmad, A., Bakri, P., Mokhtar, M. R., and Khalil, N. (2014). Solid waste collection routes optimization via GIS techniques in Ipoh city , Malaysia. Procedia Engineering, 77(December 2013), 20–27.
DOI 10.1016/j.proeng.2014.07.023

O’Connor, D. L. (2013). Solid waste collection vehicle route optimization for the city of Redlands , California. University of Redlands

Risti´c, G., Djordjevi´c, A., Hristov, S., Umiˇcevi´c, P., Petkovi´c, A., and L.Miloˇsevi´c. (2015). Methodology for route optimization for solid waste collection and transportation in urban areas. Working and Living Environmental Protection, 12(2), 187–197

Sallem, R., and Rouis, M.J. (2017). Optimization of household waste collection routes using GIS: Case study of El Bousten District, Commune of Sfax , Tunisia. Current World Environment, 12(1), 53–60

Sulemana, A., Donkor, E.A., Forkuo, E.K., and Oduro-Kwarteng, S. (2019). Effect of optimal routing on travel distance , travel time and fuel consumption of waste collection trucks. Management of Environmental Quality, 30(4),
DOI 10.1108/MEQ-07-2018-0134

Sulemana, A., Donkor, E. A., Forkuo, E. K., and Oduro-kwarteng, S. (2018). Optimal routing of solid waste collection trucks: A review of methods, 2018.
DOI 10.1155/2018/4586376

Tavares, G., Zsigraiova, Z., Semiao, V., and Carvalho, M. G. (2009). Optimisation of MSW collection routes for minimum fuel consumption using 3D GIS modelling. Waste Management, 29(3), 1176–1185.
DOI 10.1016/j.wasman.2008.07.013

Tchobanoglous, G., Theisen, H., and Vigil, S. A. (1993). Integrated Solid Waste Management. (B. J. Clark & J. M. Morriss, Eds.) (International). New York: McGraw-Hill, Inc

Zsigraiova, Z., Semiao, V., & Beijoco, F. (2013). Operation costs and pollutant emissions reduction by definition of new collection scheduling and optimization of MSW collection routes using GIS. The case study of Barreiro, Portugal. Waste management, 33(4), 793-806