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Modelling of Taxi Dispatch Problem Using Heuristic Algorithms

机译:使用启发式算法建模出租车分派问题

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Taxi routing is a complex task that involves the pickup and delivery by a fleet of vehicles in a specified time, taking into account many parameters and criteria. This paper describes issues related to this problem. It proposes a formal description of the problem and a goal function using a wide variety of criteria. Three heuristic algorithms: Ant Colony Optimization, Artificial Bee Colony and Genetic Algorithm are selected for testing. As a result three variants of these algorithms are implemented: Ant Colony System (ACS), Predict and Select - Artificial Bee Colony (PS-ABC) and Genetic Algorithm (GA) to conduct a survey. Operators used in the algorithms are adapted to a taxi dispatch problem. The analysis is performed in order to find the best parameters for the algorithms according to the data input. Finally, the efficiency of the algorithms are compared in order to determine the best algorithm. In several experiments the Ant Colony System outperforms any other algorithm presented here with respect to taxi working time currently in service.
机译:出租车路由是一项复杂的任务,涉及在指定时间内由一支车辆队列的拾取和交付,考虑到许多参数和标准。本文介绍了与此问题有关的问题。它提出了解决问题的正式描述和使用各种标准的目标函数。三种启发式算法:蚂蚁殖民地优化,选择人工蜂殖民地和遗传算法进行测试。结果,实施了这些算法的三种变体:蚁群系统(ACS),预测和选择 - 人造蜜蜂菌落(PS-ABC)和遗传算法(GA)进行调查。算法中使用的操作员适用于出租车派遣问题。执行分析,以便根据数据输入找到算法的最佳参数。最后,比较算法的效率以确定最佳算法。在几个实验中,蚁群系统优于此处就目前服务的出租车工作时间提供的任何其他算法。

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