Location-Allocation Models
Also known as: facility location, p-median problem, maximal covering location problem, yer-tahsis modelleri
Location-allocation models decide where to place a set of facilities and simultaneously assign demand points to them so as to optimize an objective such as total travel cost, worst-case distance, or population covered. Rooted in the operations-research work of Cooper (1963) and Hakimi (1964) and central to network GIS, they answer questions like where to site warehouses, hospitals, fire stations, or schools to best serve a spatially distributed population.
Key highlights
- Optimizes facility siting and demand assignment jointly over a real network.
- Multiple objectives (efficiency, equity, coverage) via p-median/p-center/covering.
- Produces actionable outputs: chosen sites plus their service areas.
- Well-grounded in operations research with mature solution methods.
Intuition
This section is available to Pro members. Upgrade to Pro
How it works
This section is available to Pro members. Upgrade to Pro
When to use it
Use location-allocation for siting public or private facilities — hospitals, clinics, fire/EMS stations, schools, warehouses, retail outlets, charging stations — when you must choose locations and service assignments to optimize access, cost, coverage, or equity over a real network. Pick the model to match the goal: p-median for efficiency (minimize total travel), p-center for equity (protect the worst-served), maximal covering for service within a standard. It needs a good network/cost model and demand weights, and results are sensitive to candidate-site definitions and the cost metric. For multi-criteria suitability (combining many map layers rather than a single travel objective), GIS-MCDA is complementary; for routing once facilities exist, use shortest-path/vehicle-routing methods.
Strengths & limitations
- Optimizes facility siting and demand assignment jointly over a real network.
- Multiple objectives (efficiency, equity, coverage) via p-median/p-center/covering.
- Produces actionable outputs: chosen sites plus their service areas.
- Well-grounded in operations research with mature solution methods.
- Large instances are NP-hard, needing heuristics rather than exact solutions.
- Requires an accurate network cost model and demand weighting.
- Sensitive to the set of candidate sites and the chosen cost metric.
- Static: typically ignores future demand change unless modelled explicitly.
Common pitfalls
This section is available to Pro members. Upgrade to Pro
Applications
This section is available to Pro members. Upgrade to Pro
Frequently asked
What is the difference between p-median and p-center?
The p-median minimizes the total (population-weighted) travel cost to facilities — an efficiency objective. The p-center minimizes the maximum distance any demand point travels — an equity/worst-case objective. They can yield very different solutions, so the choice should reflect whether you care about average access or protecting the worst-served.
Does it use straight-line or network distance?
Properly, network distance or travel time, computed over the road network, because real access follows routes, not crow-flight lines. Using Euclidean distance is a simplification that can misplace facilities, especially where the network is irregular.
How is this different from GIS-MCDA suitability?
Location-allocation optimizes a single network objective (cost/coverage) and assigns demand. GIS-MCDA combines many weighted criteria layers into a suitability surface for siting. They are complementary: MCDA can screen suitable areas, and location-allocation can then optimize exact sites and service assignment.
Sources
- 1.Cooper, L. (1963). Location-allocation problems. Operations Research, 11(3), 331–343.
- 2.Hakimi, S. L. (1964). Optimum locations of switching centers and the absolute centers and medians of a graph. Operations Research, 12(3), 450–459.
You have read it. What now?
Cite this page
ScholarGate. (2026, June 2). Location-Allocation. ScholarGate. https://scholargate.app/spatial-analysis/location-allocation