Quantum-inspired Evolutionary Algorithm for Transportation Network Design Optimization

被引：2
|
作者：
Yan Xinping, r [1 ]
Lv Nengchao [1 ]
Liu Zhenglin [2 ]
Xu Kun [1 ]
机构：
[1] Wuhan Univ Technol, Engn Ctr Transportat MOE, Wuhan 430070, Peoples R China
[2] Wuhan Univ Technol, Sch Energy & Power Engn, Wuhan 430070, Peoples R China
来源：
SECOND INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTING: WGEC 2008, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/WGEC.2008.35
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Transportation network design problem deals with how to add or improve some edges on an existing transportation network to improve traffic condition. In this study a bi-level programming model was proposed to optimize the strategy of transportation network capacity improvement in the constraint of budget. The upper level problem aims to minimize the total travel time of all transportation travelers, while the lower level model is users' equilibrium transportation assignment model. A quantum-inspired evolutionary algorithm was employed to solve the problem. The result of numerical experiment indicated that the proposed model can reduce total travel time by searching optimal solution and the QEA is more efficient than other heuristic algorithm.
引用
收藏
页码：189 / +
页数：2
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