Optimal Municipal Bus Routing Using a Genetic Algorithm
Efficient utilization of mass transit is a cost effective and environmentally sound means to meet urban transportation needs. One of the most common forms of mass transit is the municipal bus. The process of bus route assignment is extremely complex when issues such as efficiency, ridership, access, etc. are considered. This paper describes a genetic algorithmic (GA) approach for the efficient design of municipal bus routes. For complex problems, the GA-based algorithm is more efficient and flexible than manual or other computer-based processes. The genetic algorithm in this study finds an optimal or near optimal route based on the features of a given bus route service area. For this study, four features were considered: ridership, the significance of visited sites, distance, and impediments. Other attributes such as fuel efficiency, time of travel, etc. can be added to the system, and the user can change the relative importance of attributes to allow for a “what if” type of analysis.
KeywordsGenetic Algorithm Optimal Route Vehicle Route Problem Short Path Algorithm Common Node
Unable to display preview. Download preview PDF.
- Goldberg, David E. 1989 “Genetic Algorithms in Seareh, Optimization, and Machine Learning.” Reading, MA: Addison-Wesley Publishing.Google Scholar
- Hooper, Dale C., Flann, Nicholas S., and Fuller, Stephanie R, “Recombinative Hill-Climbing: A Stronger Seareh Method for Genetic Programming.” Genetic Programming 1997: Proceedings of the Second Annual Conference, 174–179 (1997).Google Scholar
- Kuo, J., “Optimal Bus Route Search Using Genetic Algorithrns.” Areport submitted in partial fulfillment of the requirements for the degree of a Master of Science in Computer Science, Utah State University. Logan, Utah. (1997).Google Scholar
- van Nes R., Hamerslag, R., and Immers, B. H., “Design of Publie Transport Networks.” Trans. Res. Rec. No. 1202, 74–83. (1986).Google Scholar