Optimizing bus services with variable directional and temporal demand using genetic algorithm
Document Type
Article
Publication Date
7-1-2016
Abstract
As a major mode choice of commuters for daily travel, bus transit plays an important role in many urban and metropolitan areas. This work proposes a mathematical model to optimize bus service by minimizing total cost and considering a temporally and directionally variable demand. An integrated bus service, consisting of all-stop and stop-skipping services is proposed and optimized subject to directional frequency conservation, capacity and operable fleet size constraints. Since the research problem is a combinatorial optimization problem, a genetic algorithm is developed to search for the optimal result in a large solution space. The model was successfully implemented on a bus transit route in the City of Chengdu, China, and the optimal solution was proved to be better than the original operation in terms of total cost. The sensitivity of model parameters to some key attributes/variables is analyzed and discussed to explore further the potential of accruing additional benefits or avoiding some of the drawbacks of stop-skipping services.
Identifier
84978674844 (Scopus)
Publication Title
Journal of Central South University
External Full Text Location
https://doi.org/10.1007/s11771-016-3232-8
e-ISSN
22275223
ISSN
20952899
First Page
1786
Last Page
1798
Issue
7
Volume
23
Recommended Citation
Qu, He zhou; Chien, Steven I.Jy; Liu, Xiao bo; Zhang, Pei tong; and Bladikas, Athanassios, "Optimizing bus services with variable directional and temporal demand using genetic algorithm" (2016). Faculty Publications. 10423.
https://digitalcommons.njit.edu/fac_pubs/10423
