Research Information System
Transportation Research Part D: Transport and Environment, vol.157, 2026 (SCI-Expanded, SSCI, Scopus)
Rapid urbanization makes traditional, fixed-frequency municipal solid waste (MSW) collection highly inefficient, causing severe operational and environmental impacts. This study develops a GIS-based optimization framework for high-density MSW collection integrating spatial demand analysis with mixed-frequency routing and scheduling. Demand heterogeneity was quantified using GIS-based hot spot analysis to assign collection frequencies, and a standard GIS network solver was reconfigured to emulate periodic capacitated arc routing under high-density conditions. The resulting mixed-frequency plan was evaluated against the municipality’s fixed-frequency system in the Çiğli District of İzmir. Spatial optimization reduced the number of collection points by 31.63% and container inventory by 25.69%. Operational performance improved through an 18.75% reduction in collection time and a 19.02% reduction in fuel consumption. Correspondingly, collection-related CO2 emissions decreased by 19.91%, contributing 7.54% toward decarbonization targets. By combining low computational cost with the simplicity of a “no-code” GIS environment, this approach offers a scalable, practical solution to improve urban service logistics.