PRIORITIZING AND SCHEDULING ROAD PROJECTS BY GENETIC ALGORITHM

The optimum timetable for implementing a set of road projects so as to achieve maximum investment effectiveness can be found by ranking or G oal Programming (GP) under the assumption that the payoffs of all the projects are divisible and proportional to their proportions undertake n. This assumption is valid for upgrading projects (Type I) but not fo r new ones (Type 2). When this difference is taken into account, neith er ranking nor GP are effective methods to find the optimum timetable. This paper develops a genetic algorithm (GA) to address this problem. The GA uses the ranking vector of the projects as a GA individual and then transforms it into a project proportion matrix by imposing the b udget constraint. Experiments show that the GA can find the optimum so lution with an acceptable accuracy, and when the projects are differen tiated between Type 1 and 2, the GA finds the optimum timetable that i s different from that in the case of all Type 1 projects.