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