Some Computational Insights on the Optimal Bus Transit Route Network Design Problem

The objective of this paper is to present some computational insights based on previous extensive research experiences on the optimal bus transit route network design problem (BTRNDP) with zonal demand aggregation and variable transit demand. A multi-objective, nonlinear mixed integer model is developed. A general meta-heuristics-based solution methodology is proposed. Genetic algorithms (GA), simulated annealing (SA), and a combination of the GA and SA are implemented and compared to solve the BTRNDP. Computational results show that zonal demand aggregation is necessary and combining metaheuristic algorithms to solve the large scale BTRNDP is very promising.


Subject(s):
Issue Date:
2008
Publication Type:
Journal Article
PURL Identifier:
http://purl.umn.edu/206963
Published in:
Journal of the Transportation Research Forum, Volume 47, Number 3
Page range:
60-75
Total Pages:
16




 Record created 2017-04-01, last modified 2017-08-28

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