Optimization of Paper Waste Collection
Optimization of Paper Waste Collection
in Alcalá de Henares, Spain
in Alcalá de Henares, Spain
Embedded Files
This project applies GIS to design an optimized paper recycling collection system for the city of Alcalá de Henares, Spain. The study addresses a hypothetical scenario in which the city lacks paper recycling containers and requires a spatially optimized system for container placement and collection routes.
Using spatial analysis and network modeling, the project estimates citywide paper waste generation, determines the number of containers required, and identifies optimal container locations. Residential demand was represented using building entrance points derived from the CartoCiudad dataset, allowing the analysis to model waste generation at a detailed spatial scale.
The project then applied ArcGIS Pro network analysis tools to evaluate multiple container location strategies and design efficient truck routes for waste collection. By combining waste generation estimates, container capacity limits, and transportation constraints, the analysis demonstrates how GIS can support more efficient urban service planning.
Results
The analysis estimated that Alcalá de Henares generates approximately 670,900 liters of paper waste per week, requiring approximately 210 recycling containers with a capacity of 3,200 liters each.
Three Location–Allocation models were tested to determine the best container placement strategy.
The Minimize Impedance model prioritized minimizing walking distance between residents and containers. While this solution provided full population coverage, many containers exceeded their capacity limits.
The Maximize Attendance model focused on placing containers where the highest recycling participation was expected within a 500-meter walking threshold. This approach reduced total travel distance but left roughly 20% of residents without access.
The Maximize Capacitated Coverage model provided the most balanced solution. This model served approximately 98.5% of the population while respecting container capacity constraints, ensuring that nearly all residents had access to a recycling container within a reasonable walking distance.
After selecting the final container locations, a Vehicle Routing Problem (VRP) analysis was used to design collection routes. The optimized system requires nine truck routes, each collecting approximately 26 containers within a three-hour evening collection window. Most routes can be completed in under two hours, indicating that the system is operationally feasible and efficient.
Maximize capacitated coverage
Maximize capacitated coverage
9-Route Location-Allocation Map
9-Route Location-Allocation Map
Key Maps & Visualizations
Spatial distribution of residential demand points using building entrance data
Location–Allocation results for the three container placement models
Connection lines illustrating distances between residential demand points and assigned containers
Final map of optimized recycling container locations across the city
Vehicle Routing Problem analysis showing optimized truck collection routes
Route sequence maps displaying container pickup order and travel distance
GIS Editing & Processing Tools
Network Dataset creation and routing analysis
Location–Allocation modeling
Vehicle Routing Problem (VRP) analysis
Spatial joins and demand weighting
Attribute table management and statistical calculations
Data preprocessing and analysis using Python
Shapefile creation and feature layer management
Technical Tools & Data Sources
ArcGIS Pro
CartoCiudad building entrance dataset
Population data by census section
Street network datasets for routing analysis
Waste generation statistics from Madrid municipal datasets
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OCT Madrid Land Use
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+ BICI Córdoba
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