GUI Bin, ZHOU Wei, WANG Jian-hua, ZHOU Li, WANG Xia-sen. Bi-level programming model of decision optimization of reconstruction and expansion for highway network[J]. Journal of Traffic and Transportation Engineering, 2012, 12(5): 79-84. doi: 10.19818/j.cnki.1671-1637.2012.05.011
Citation: GUI Bin, ZHOU Wei, WANG Jian-hua, ZHOU Li, WANG Xia-sen. Bi-level programming model of decision optimization of reconstruction and expansion for highway network[J]. Journal of Traffic and Transportation Engineering, 2012, 12(5): 79-84. doi: 10.19818/j.cnki.1671-1637.2012.05.011

Bi-level programming model of decision optimization of reconstruction and expansion for highway network

doi: 10.19818/j.cnki.1671-1637.2012.05.011
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  • Author Bio:

    GUI Bin(1974-), male, senior engineer, doctoral student, +86-29-82334898, guibinmot@sina.com

    ZHOU Wei(1959-), male, professor, PhD, +86-29-82334434, zhw59@hotmail.com

  • Received Date: 2012-05-26
  • Aiming at the reconstruction and expansion problems of highway network, the factors such as technique, fund, environmental protection and operation efficiency were considered during the decision optimization process. The minimum traffuc volume of highway network system was taken as the objective function of upper-level model, the minimum trip time was taken as the objective function of lower-level model, the service level of road section, land occupancy status and construction investment were taken as constraint conditions, and a bi-level programming model of decision optimization of reconstruction and expansion for highway network was set up. Genetic algorithm was used to solve the model, and empirical analysis was carried out by using the example data of Northern Jiqing Highway. Calculation result shows that the expansion optimization indexes of Jinan-Zibo section, Zibo-Qingzhou section and Qingzhou-Weifang section for Northern Jiqing Highway are 2.15, 4.09 and 3.54 respectively, while the newly-built optimization indexes of the road sections are 1.87, 3.09 and 2.73 respectively. The expansion optimization index is higher than the newly-built optimization index for each road section, which is close to actual experience, so the model is effective.

     

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