Urban Logic
[03c]
Urban Simulation
[Desciption]
A district-level optimisation model balancing the supply and demand of school facilities in Riyadh over a 50-year horizon. Offers two optimisation approaches — area-based and land parcel-based — sensitive to actual land availability building regulations and pre-designed facility prototypes.
[Model Objective]
A district-level optimisation model that balances the supply and demand of school facilities in Riyadh over a 50-year horizon, using projected school-age population as its demand input. The model moves beyond the conventional practice of applying a fixed global area-per-student ratio — instead offering two optimisation approaches that are sensitive to actual land availability, building regulations, and pre-designed facility prototypes. While developed for general education provision in Riyadh, the optimisation logic is generic and directly applicable to any public or private facility type where demand is population-driven and supply is land-constrained.
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PhD Research
2023
Education Provision Optimisation Model
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The model monitors optimised provision standards, required land area, and recommended facility prototypes by district, education stage, and gender across the full projection horizon. Applied to sample districts in Riyadh, results show that established districts already hold excess supply capacity, while peripheral growth districts face significant future deficits. The two optimisation functions consistently produce comparable outcomes, with the parcel-based approach offering greater implementation precision for district-level decision making.
[Model Components]
Area-based optimisation function — calibrates the m² per student standard across 5-year time steps to match projected demand within available land · Land parcel-based optimisation function — matches pre-designed building prototypes (22 school prototypes × 2 genders = 44 alternatives) to specific available land parcels for district-level precision · Building regulation constraint module (FAR, MBFAR) · Land preservation ratio controller · Multi-scenario testing across fertility, migration, and mobility assumptions
[Model Results]
The model monitors optimised provision standards, required land area, and recommended facility prototypes by district, education stage, and gender across the full projection horizon. Applied to sample districts in Riyadh, results show that established districts already hold excess supply capacity, while peripheral growth districts face significant future deficits. The two optimisation functions consistently produce comparable outcomes, with the parcel-based approach offering greater implementation precision for district-level decision making.
[Model Components]
Local Optimisation · Land Consumption Ratio Control · Floor Area Ratio (FAR) & Maximum Building Footprint Area Ratio (MBFAR) Constraints · Prototype-Based Supply Matching · Multi-Scenario Sensitivity Analysis
[Tags]
["Optimisation", "Education Provision", "Land Use", "ABM", "AnyLogic"]