Optimization of grid transit system in heterogeneous urban environment

Current analytic models for optimizing urban transit systems tend to sacrifice geographic realism and detail in order to obtain their solutions. The model presented here shows how an optimization approach can be successful without oversimplifying the spatial characteristics and demand patterns of urban areas. This model is designed to optimize a grid transit system in a heterogeneous urban environment whose demand and supply characteristics may vary arbitrarily among adjacent zones. Network characteristics (route and station locations) and operating headways are found that minimize the total cost, including supplier and user costs. Irregular many-to-many demand patterns, zonal variations in route costs, and vehicle capacity constraints are considered in a sequential optimization process.