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Genetic Search of Pickup and Delivery Problem Solutions for Self-driving Taxi Routing

机译:自行车出租车路线的拾取和交付问题解决方案的遗传搜索

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Self-driving cars belong to rapidly growing domain of cyber-physical systems with many open problems. In this paper, we study routing problem for taxis. In mathematical terms, it is well-known Pickup and Delivery problem (PDP). We use with the standard small-moves technique, which is to apply small changes to a solution for PDP in order to obtain a better one; and an approach that works with small-moves as mutations in genetic algorithms. We propose a strategy-based framework for managing set of small changes and suggest different strategies. We tested algorithms for routing on real-world dataset on taxi orders to airports in United Kingdom. The results show that algorithms using mixed strategies outperform algorithms using a single small move.
机译:自动驾驶汽车属于具有许多公开问题的网络物理系统的快速生长领域。在本文中,我们研究了出租车的路由问题。在数学术语中,它是众所周知的拾取和交付问题(PDP)。我们使用标准的小型移动技术,这是对PDP的解决方案应用小变化,以便获得更好的解决方案;一种与遗传算法中的小动作有效的方法。我们提出了一个基于战略的框架,用于管理一组小型变化,并提出了不同的策略。我们测试了在英国的机场上的现实世界数据集路由进行路由算法。结果表明,使用混合策略的算法使用单个小型移动优于算法。

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