Optimizing Equitable Public-Facility Allocation

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How it works
• Drag any house → all facilities auto-reposition to serve it best
• Drag a facility directly → its Voronoi cell & gradients update live
• Distances computed via d = √(Δx² + Δy²) on a 10 m grid

• C1 dense / high fire-risk

• C2 market / medium

• C3 low-density / low

• C4 distributed

• 🚒 Fire

• 🚑 Ambulance

• 🏥 Health 1

• 🏥 Health 2

• 🏫🏪🕌 POIs (schools, shops, mosques) — decorative, not in calculation

• Each facility has its own colour gradient — near = light, far = dark

• Voronoi cell = all houses closer to that facility than any other

• Hover a house → see the Pythagoras triangle & all distances

Coverage gradient

close (light)far (dark)

C1 houses (15) C2 houses (9) C3 houses (6) C4 houses (15)

Voronoi cells 10 m grid

POIs (schools/shops/mosques)

Optimizing Equitable Public-Facility Allocation in a Residential District Using Voronoi Tessellation and Euclidean Distance: A Computational-Geometry Approach

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Coverage gradient

Measured distance