A heuristic method for land-use plan generation in planning support systems

1. A heuristic method for land-use plan generation in planning support systems Theo Arentze, Aloys Borgers and Harry Timmermans

2. Outline • Background and objectives • The proposed method • Illustration • Conclusions and future research

3. Background • Urban land-use planning models can be used to generate plan alternatives • The models consist of: • Some zoning system (i.e., a grid of cells) • A suitability function • An allocation algorithm • The suitability function is not well-suited to evaluate spatial configurations of facilities (e.g., schools, shopping centers)

4. Objective • To develop and explore a method to combine location-allocation models and land-use models for land-use plan generation

5. Location-allocation models • Characteristics of user-attracting facility systems: • Users choose and travel to facility locations • Performance of the facility network depends on demand attracted • The problem considered in discrete-space models: • Find p locations among n candidate locations that maximize a given objective function (within constraints)

6. Location-allocation models Land-use models Combining the models • Retail facilities • School facilities • Green facilities • Etc. • Housing high density • Housing medium density • Housing low density • Industry • Nature • Etc. • Interchange heuristic • Swapping heuristic

7. Initial allocation score of distance from cell i to nearest cell with land-use j’ score of land characteristic k of cell i for land-use j Optimize allocation Compare Swap? score of the adjacency to land-use j’ for land-use j in cell i The Swapping heuristic

8. Step 1. Choose a macro-strategy Centralized Semi-centralized Decentralized Step 2. Given a macro-strategy, find optimal locations The Interchange heuristic

9. Random initial solution Evaluate substitutions Step 2. Given a macro-strategy, find optimal locations

10. Example of a maximum-covering solution Housing density is demand weight Potential housing has average demand weight

11. Initial Interchange Choice options reduce Initial Interchange Information increases Initial Swap Integrating the two heuristics • Allocate Facility 1 • Allocate Facility 2 • ……. • Allocate area-type land-uses

12. Illustration Centralized Semi-centralized De-centralized Trade-off: Economic versus Accessibility objectives

13. Conclusions • The new method integrates the Interchange and Swapping heuristic • Suitability of land-uses is evaluated: • On a cell-basis for area-type landuses • On a location-network basis for facility-type land-uses • The distinction between macro-strategies enables generating meaningfull plan alternatives for multi-criteria analysis

14. Future research • Refining the objective function of the location-allocation model • Incorporating the planning of the transport system • Simulating behavior of users under land-use plan conditions