Optimizations of network layout and transport service frequencies in view of interests of transit line operators and utilizers

Xiaojing ZHU; Xuesong FENG; Lukai ZHANG; Weixin HUA

doi:10.5604/01.3001.0013.5619

Authors

Xiaojing ZHU Beijing Jiaotong University, School of Traffic and Transportation, Beijing, P.R. China Author
Xuesong FENG Beijing Jiaotong University, School of Traffic and Transportation, Beijing, P.R. China Author
Lukai ZHANG Beijing Jiaotong University, School of Traffic and Transportation, Beijing, P.R. China Author
Weixin HUA Beijing Jiaotong University, School of Traffic and Transportation, Beijing, P.R. China Author

DOI:

https://doi.org/10.5604/01.3001.0013.5619

Keywords:

transit network layout design, transportation service, service optimization, interests of transit line operators, interests of utilizers, simulated annealing algorithm, genetic algorithm

Abstract

Layouts of bus networks in cities are always irrational currently, transport service frequencies also need to be optimized according to the real network layouts, operation conditions and travel experience of passengers, so it is essential to optimize bus transit network layouts and transport service frequencies systematically. Different stakeholders are involved in the optimization of urban bus transit network layouts like the government, operators and passengers, whose interests are always contradictory. In order to optimize transit network layout and service frequencies from the view point of operators and utilizers, this research constructs a multi-objective model and proposes a solution algorithm. The proposed multi-objective model is established from the perspective of operators with the goal of minimizing total operating costs for one day, and from the perspective of the utilizers to minimize the total travel time, respectively. Also with the application of electric bus in cities, buses in this research are electric buses all for green travel. Moreover, a solution algorithm is proposed in this research to solve the proposed multi-objective model with simulated annealing algorithm and genetic algorithm. Simulated annealing algorithm is used as the main framework of the solution algorithm from the perspective of operators to minimize operating costs, while genetic algorithm is used as the subroutine of simulated annealing algorithm to optimize total travel time. Verification of the proposed model and the solution algorithm is based on an intuitive network. The application results of a numerical experiment verified that the proposed optimization model and the solution algorithm are able to optimize the network layout and service frequencies at the same time.

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