Networks and Spatial Economics

, Volume 12, Issue 3, pp 441-480

First online:

Hybrid Evolutionary Metaheuristics for Concurrent Multi-Objective Design of Urban Road and Public Transit Networks

  • Elnaz MiandoabchiAffiliated withDepartment of Industrial Engineering, Amirkabir University of Technology
  • , Reza Zanjirani FarahaniAffiliated withDepartment of Informatics and Operations Management, Kingston Business School, Kingston University Email author 
  • , Wout DullaertAffiliated withInstitute of Transport and Maritime Management AntwerpAntwerp Maritime Academy
  • , W. Y. SzetoAffiliated withDepartment of Civil Engineering, The University of Hong Kong

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This paper addresses a bi-modal multi-objective discrete urban road network design problem with automobile and bus flow interaction. The problem considers the concurrent urban road and bus network design in which the authorities play a major role in designing bus network topology. The road network design deals with the decision making for new street constructions, lane additions to existing streets, lane allocations for two-way streets, and the orientations and locations of one-way streets. The bus network design is performed by keeping the terminal stations of the existing bus lines unchanged and redesigning the forth and back routes of each line. Four measures, namely user benefit, the demand coverage of the bus network, the demand share of the bus mode, and the average travel generalized cost of bus passengers, are used to evaluate the network design scenarios. The problem is formulated as a multi-objective optimization model in which a modal-split/assignment model is included to depict the mode and route choice behaviors of travelers. The model is solved by the hybrid genetic algorithm and the hybrid clonal selection algorithm. The performance of these algorithms is presented and investigated by solving a number of test networks.


Bimodal Transit network design Road network design Multi-objective optimization Elastic demand Hybrid metaheuristics