The Memetic algorithm for the optimization of urban transit network

The Memetic algorithm for the optimization of urban transit network
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用于优化城市交通网络的 Memetic 算法

DOI:
10.1016/j.eswa.2014.11.056
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发表时间:
2015-05
影响因子:
8.5
通讯作者:
Rong Jiang
Rong Jiang
中科院分区:
计算机科学1区
文献类型:
--
作者:
Hang Zhao;Wangtu Xu;Rong Jiang

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本文采用Memetic算法(MA)来优化城市交通网络。针对城市公交网络的最优线路配置和服务频次,所提出的数学模型的目标函数是最小化乘客(用户)成本,最多减少未满足的乘客需求。 MA 是最近发展的进化计算算法之一。它嵌入了基于经典遗传算法(GA)的局部搜索算子,以提高计算性能。我们用两个单链表(SLL)表示解决方案,并设计四种类型的局部搜索算子:2-opt move(A型)、2-opt move(B型)、交换移动和重定位移动,以获得GA更好的染色体。同时,提出了一种有效的试错程序来验证局部搜索算子,以提高搜索效率。该算法已经通过现有文献中报告的基准问题进行了测试。将我们的算法获得的结果与已被证明有效的传统算法进行比较,表明所提出的算法相对于其他算法可以提高计算性能。
This paper employs the Memetic algorithm (MA) to optimize the urban transit network. Aiming at the optimal route configuration and service frequency for the urban transit network, the objective function of the proposed mathematical model is to minimize the passenger (user) cost and to reduce the unsatisfied passenger demand at most. MA is one of the recent growing evolutionary computation algorithms. It is imbedded with the local search operator based on the classical genetic algorithm (GA) to improve the computational performance. We represent the solution with two single link lists (SLL), and design four types of local search operators: 2-opt move (Type A), 2-opt move (Type B), swap move and relocation move to obtain the better chromosomes for the GA. At the same time, an effective try-an-error procedure for verifying the local search operator is presented to increase the search efficiency. The algorithm has been tested with benchmark problems reported in the existing literatures. Comparing the results obtained by our algorithm and traditional algorithms which have been proved to be efficient, it demonstrates that the proposed algorithm could improve the computational performance relative to other algorithms.
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