Title :
Quantum-Inspired Evolutionary Algorithm for Transportation Network Design Optimization
Author :
Xinping Yan ; Nengchao Lv ; Zhenglin Liu ; Kun Xu
Author_Institution :
Eng. Center for Transp. of MOE, Wuhan Univ. of Technol., Wuhan
Abstract :
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.
Keywords :
evolutionary computation; mathematical programming; minimisation; network theory (graphs); quantum computing; road traffic; search problems; transportation; travelling salesman problems; bi-level programming model; budget constraint; equilibrium transportation assignment model; heuristic algorithm; quantum-inspired evolutionary algorithm; search problem; total travel time minimization; traffic condition; transportation network design optimization problem; Design optimization; Evolutionary computation; Heuristic algorithms; Mathematical model; Power engineering and energy; Quantum computing; Roads; Telecommunication traffic; Traffic control; Transportation; Quantum-inspired Evolutionary Algorithm; bi-level programming; network design problem;
Conference_Titel :
Genetic and Evolutionary Computing, 2008. WGEC '08. Second International Conference on
Conference_Location :
Hubei
Print_ISBN :
978-0-7695-3334-6
DOI :
10.1109/WGEC.2008.35
