Scenario Analysis with Facility Location Optimization

In a densely populated city, effective land uses and redevelopment is critical to enable growth, development and renewal in all aspects of city planning. For instance, sufficient housing provision, adequate supporting infrastructure and accessible amenities are required to support population growth. Urban planners face the issue of where to locate facilities (e.g. clinics, elder/childcare centres and schools) such that they can best serve their intended target population. This presents the problem of arriving at a distribution of facilities that maximally optimizes coverage to target populations while minimizing the number of facilities to build. In this paper, we proposed a planning decision support platform for city planning with new flexible mixed integer programming models at the core and an interactive interface at the front-end that is integrated with a Geo-Information System. The system can generate scenarios, calculate travel time/distance based on road network, call and solve optimization models, and do scenario comparison and sensitivity analysis. Using existing and projected data for population growth and schools as an example, we examined the effectiveness and performance of our decision system and optimization approach for city planning. The results show that our optimization model and approach can solve real problems within a reasonable timeframe and can provide valuable insights for planners to inform land use planning decisions.