Using GIS, genetic algorithms, and visualization in highway development

A model for highway development is presented, which uses geographic informa tion systems (GIS), genetic algorithms (GA), and computer visualization (CV ). GIS serves as a repository of geographic information and enables spatial manipulations and database management. GAs are used to optimize highway al ignments in a complex search space. CV is a technique used to convey the ch aracteristics of alternative solutions, which can be the basis of decisions . The proposed model implements GIS and GA to find an optimized alignment b ased on the minimization of highway costs. CV is implemented to investigate the effects of intangible parameters, such as unusual land and environment al characteristics not considered in optimization. Constrained optimization using GAs may be performed at subsequent stages if necessary using feedbac k received from CVs. Implementation of the model in a real highway project from Maryland indicates that integration of GIS, GAs, and CV greatly enhanc es the highway development process.