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A Particle Swarm Optimization Algorithm for Bilevel Programming Models inUrban Traffic Equilibrium Network Design

机译:城市交通均衡网络设计中双层规划模型的粒子群优化算法

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摘要

A new algorithm is proposed to solve one usual model of bilevel programmingmodels in urban transportation equilibrium network design. The upper model issolved by PSO and the lower model is solved by Frank-Wolfe, then iterations arecontinuously progressed between them so that the global optimum solution can beapproximated. The algorithm is illustrated with an example and compared with otheralgorithms. Results demonstrate that the effectiveness of this algorithm, whileiterations and extra computational burdens are not so heavy.
机译:提出了一种新的算法来求解城市交通平衡网络设计中一个常见的双层规划模型模型。上层模型由PSO求解,下层模型由Frank-Wolfe求解,然后在它们之间连续进行迭代,以便可以逼近全局最优解。举例说明该算法,并将其与其他算法进行比较。结果表明,该算法的有效性,迭代次数和额外的计算负担都不那么重。

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