Transit Network Optimization: Minimizing Transfers and Maximizing Service Coverage with an Integrated Simulated Annealing and Tabu Search Method

Ike Ubaka · Albert C. Gan

21 citations0/0 files storedTransportation Research Record Journal of the Transportation Research Board

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Transportation Planning and Optimization Vehicle Routing Optimization Methods Transportation and Mobility Innovations

Abstract

This paper presents a mathematical methodology for transit route network optimization. The goal is to provide an effective computational tool for optimization of a large-scale transit route network. The objectives are to minimize transfers and maximize service coverage. Formulation of the method consists of three parts: representation of transit route network solution search spaces, representation of transit route and network constraints, and a stochastic search scheme capable of finding the expected global optimal result on the basis of an integrated simulated annealing, tabu, and greedy search algorithm. The methodology has been tested with published solutions to benchmark problems and applied to a large-scale realistic network optimization problem in Miami–Dade County, Florida.

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References

1986Bus network design 1998Urban Bus Transit Route Network Design Using Genetic Algorithm 1980Evaluation and optimization of urban public transportation networks 1995Hybrid route generation heuristic algorithm for the design of transit networks 1979Some Issues Relating to the Optimal Design of Bus Routes 2002Genetic algorithms in bus network optimization 2002Optimal Route Network Design for Transit Systems Using Genetic Algorithms 2003Optimal Time Transfer in Bus Transit Route Network Design Using a Genetic Algorithm

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