DocumentCode :
2682170
Title :
Model for road network equilibrium bi-level programming based on rough genetic algorithm
Author :
Liangzhi, Zhang ; Lutao, Bai
Author_Institution :
Dept. of Traffic & Logistic Eng., Shandong Jiaotong Univ., Jinan, China
Volume :
5
fYear :
2010
fDate :
27-29 March 2010
Firstpage :
83
Lastpage :
85
Abstract :
In the traffic system with flow guidance, travelers can choose their paths according to both guidance information and their experience. In this paper, based on the relationship between the effects of traffic guidance and the construction cost, the optimization plan is established as a bi-level program. The objective function at the upper level is defined as the total travel time on the network, plus total investment costs of link capacity expansions. The lower level problem is formulated as a stochastic user equilibrium model. General genetic algorithm combined with rough set theory is used to find the optimal solution. Attributes reduction of rough set is adopted to filtrate new chromosome comes from crossover operation of GA, so as to increasing seeking speed. The result of a road network example verified high efficient of the rough genetic algorithm.
Keywords :
genetic algorithms; road traffic; rough set theory; traffic information systems; construction cost; flow guidance; intelligent traffic system; investment costs; link capacity expansions; optimization plan; road network equilibrium bi-level programming; rough genetic algorithm; rough set theory; stochastic user equilibrium model; traffic guidance; traffic system; Communication system traffic control; Cost function; Design engineering; Genetic algorithms; Genetic engineering; Investments; Roads; Telecommunication traffic; Traffic control; Transportation; bi-level programming; genetic algorithm; intelligent traffic; road network equilibrium; rough set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computer Control (ICACC), 2010 2nd International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-5845-5
Type :
conf
DOI :
10.1109/ICACC.2010.5487290
Filename :
5487290
Link To Document :
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