基于遗传算法的高速公路旅游指引标志的定量化设置方法

    Quantitative Setting Method of Expressway Tourist Guide Signs Based on Genetic Algorithm

    • 摘要: 针对复杂路网条件下旅游指引标志设置缺乏理论支撑的问题,选取旅游景区的等级、游客吸引量、面积与高速公路出口至景区的行驶时间作为其指引需求的影响因素,应用灰色变权聚类理论建立了旅游景区的指引需求层次划分算法. 与以往仅根据等级划分旅游景区指引重要性的方法相比,所提出的方法综合考虑了景区的交通吸引功能,更符合驾驶员的指引需求. 以诱导效果最优为优化目标,考虑高速公路旅游指引标志的总量约束、高速公路出口至旅游景区的路径约束、所有景区在高速公路出口均至少被诱导一次的条件约束,构建数学模型并利用遗传算法求解,从而确定旅游指引标志最优布设方案.

       

      Abstract: The purpose of this research is to establish and optimize the quantization algorithm of the tourist guide signs designing for the complex road networks. The rating of tourist attractions, the amount of tourists, tourism scenic areas, the travel time from expressway exits to tourist attractions were taken as the influence factors of node demanding level for tourist attractions. Based on grey variable weight cluster theory, a division measure of guide demand for tourist regions was established,which provided the theoretical basis for choosing which tourist attractions should be guided by directional signs. Compared with the current research of considering solely the level of tourism scenic spots to classify the guide necessity, the established method considered the traffic attraction of the scenic spots, which is more aligned with the drivers' demand. Considering the total amount restriction of guide signs, the path constraints of not making turns from the exit to the tourist attraction, and the condition that all tourist regions should be guided at least once. A mathematical model was established by using the genetic algorithm to obtain the optimal inducing effect and the layout of tourist guide signs. The established method can provide the optimal layout of tourist guide signs.

       

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