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OPTIMIZED ROUTING OF TRUCKS FOR INSTITUTIONAL SOLID WASTE COLLECTION IN KUMASI, GHANA

  • 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

Abstract

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.

Keywords

Editorial History

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

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