Abstract:
Highway planning involves selection of a cost-effective corridor in an environmentally responsible manner. With the recent advances in geographic information systems (GISs), most environmental, real estate, and design databases and maps are available in the form of GIS layers. Several mathematical optimization algorithms have been developed to optimize highway alignments, among which genetic algorithms appear most promising because of their ability to avoid getting trapped in local optima. In recent studies, a GIS was integrated with genetic algorithms, enabling full exploitation of GIS features in highway alignment optimization. Those optimization models still lack some dynamic decision-making capabilities during optimal search, such as consideration of bridge cost when rivers are encountered and intersection and interchange costs when roads are encountered. A study that used a GIS as a dynamic decision-making tool in performing highway optimization is presented. Algorithms are developed to estimate costs associated with bridges, tunnels, intersections, and overpasses. A fully automated model is developed that allows dynamic data exchange between the GIS and the optimization algorithm. An example that uses real geographic information from Maryland is presented. The results indicate that consideration of bridges and intersections is significant in highway alignment optimization.
