DocumentCode
2559618
Title
Heuristic Algorithms for Capacity flexibility of urban transit networks
Author
Hang, Zhao ; Binglei, Xie ; Shi, An
Author_Institution
Res. Center of Traffic Eng., Harbin Inst. of Technol., Shenzhen, China
fYear
2012
fDate
29-31 May 2012
Firstpage
1186
Lastpage
1190
Abstract
In this paper, the concept of capacity flexibility is introduced into transit network, and the model of capacity flexibility of urban transit networks is formulated. A heuristic solution based on hybrid genetic algorithm is proposed to the model. GA-LS (Genetic algorithms with Local search) is applied to solve the model. It is also tested by a numerical example with a small transit network. The results show how the maximum additional passenger flows from each origin-destination (OD) pair are determined in a transit network and what extent the transit network supply meets the additional passenger demand in a certain level of service. These results show that the GA-LS method considerably improves the value of the objective function for same iterative times compared with the general GA, but spending more time.
Keywords
genetic algorithms; search problems; transportation; GA-LS; OD; genetic algorithms with local search; heuristic algorithms; hybrid genetic algorithm; maximum additional passenger flows; objective function; origin-destination pair; small transit network; urban transit network capacity flexibility; Biological cells; Educational institutions; Genetic algorithms; Numerical models; Roads; Vehicles; Capacity flexibility; Genetic algorithms; Local search; Transit networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location
Chongqing
ISSN
2157-9555
Print_ISBN
978-1-4577-2130-4
Type
conf
DOI
10.1109/ICNC.2012.6234694
Filename
6234694
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