A Guidance System for Wide-area Complex Disaster Evacuation based on Ant Colony Optimization

A Guidance System for Wide-area Complex Disaster Evacuation based on Ant Colony Optimization
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DOI:
10.5220/0005819502620268
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发表时间:
2016-02
期刊:
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影响因子:
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通讯作者:
Hirotaka Goto;Asuka Ohta;Tomofumi Matsuzawa;M. Takimoto;Y. Kambayashi;Masayuki Takeda
Hirotaka Goto;Asuka Ohta;Tomofumi Matsuzawa;M. Takimoto;Y. Kambayashi;Masayuki Takeda
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其他
文献类型:
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作者:
Hirotaka Goto;Asuka Ohta;Tomofumi Matsuzawa;M. Takimoto;Y. Kambayashi;Masayuki Takeda

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本文报道了我们的方法发现安全疏散路线的实际情况应用的结果。该方法是基于蚁群优化算法(ACO),它是实用的,在一个真实的情况下,海啸。蚁群算法通常被用于寻找传统方法中的疏散路线,传统方法只利用蚂蚁的行为,更频繁地通过信息素通信跟踪其他蚂蚁的踪迹。€™我们假设在受损区域有很多危险区域。例如,陆前高田是一个在2011年东日本大地震中遭到严重破坏的城市。在这种情况下,传统的方法可能会出现一些通过危险区的不安全路线。我们提出了一种基于蚁群算法的方法,计算疏散路线,避免危险区。在我们的方法中,疏散人员可以在危险区域周围放置存款除臭信息素,这使得正常的信息素无效,因此我们的方法给出了不经过危险区域的路线。我们将我们的方法作为模拟器来实施,在与陆前高田案例相同的情况下进行实验。通过实验的结果,我们表明,我们的方法减少了遭受倒塌和燃烧的建筑物的人数。
This paper reports the results of applying our approach discovering safe evacuation routes to practical situations. Our approach is based on the ant colony optimization (ACO) and it is practical in the light of a real case with a tsunami. ACO have been often employed for finding evacuation routes in traditional approaches, which only take advantage of ants behavior more frequently following traces of other ants’ through pheromone communications. We assume that there are a lot of danger zones in the damaged area. For example Rikuzentakata is a city that extensively damaged in the 2011 Great East Japan Earthquake. In such a case, the traditional approaches may present some unsafe routes through the danger zones. We have proposed an ACO based approach that calculates evacuation routes avoiding danger zones. In our approach, evacuees can deposit deodorant pheromone around danger zones, which makes normal pheromone ineffective, so that our approach gives routes not passing through the danger zones. We have implemented our approach as a simulator, conducting experiments in the same situation as the Rikuzentakata case. Through the results of the experiments, we show that our approach decreases the number of people suffering from collapsed and burning buildings.