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A MULTI-MODAL ROUTE PLANNING APPROACH WITH AN IMPROVED GENETIC ALGORITHM

机译:一种改进遗传算法的多模态路线规划方法

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The purpose of multi-modal route planning is to provide the traveler with optimal, feasible and personalized route between origin and destination, which may involve public and private transportation modes. The strategy driven approach (i.e. routing by certain predefined transfer order) is useful but can hardly provide free combination of multiple travel modes and some feasible results may be consequently missed. A genetic algorithm (GA) is proposed in this paper to solve the multi-modal route planning problem. Variable length chromosomes with several parts (subchromosome) are utilized to represent routes in multi-modal travel environment, where each part describes a kind of transportation mode. Crossover and mutation operators are redefined in single mode; two new operators, hypercrossover and hypermutation, are defined as inter-mode operation. A multi-criteria evaluation method using a p-dimensional vector to represent multiple criteria is adopted in the fitness function for selecting the optimal solutions. The experimental results show a various mode combination, and some results conform experience well.
机译:多模态路线规划的目的是为旅行者提供原籍和目的地之间的最佳,可行和个性化的路线,这可能涉及公共和私人运输模式。战略驱动方法(即,通过某些预定义的转移顺序路由)是有用的,但几乎不能提供多种旅行模式的自由组合,因此可能会错过一些可行的结果。本文提出了一种遗传算法(GA)以解决多模态路线规划问题。具有几个部件(子摩擦体)的可变长度染色体用于表示多模态行程环境中的路线,其中每个部分描述了一种运输模式。交叉和突变运算符在单一模式下重新定义;两个新的运算符,高速传递和高责任被定义为互相操作。使用P维向量的多标准评估方法以表示用于选择最佳解决方案的适应性函数中采用了多标准。实验结果显示了各种模式组合,一些结果符合良好的经验。

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