The advent of new technologies in the area of transportation has led to the creation of new business models that benefit from their capabilities. Among them, Teo Taxi, a Taxelco project, uses a unique business model: taxi drivers are employees instead of being self-employed. In addition, the company uses only electric vehicles. This shift entails new challenges regarding fleet management and process optimization. This article tackles these issues and proposes solutions to three operational problems: the dispatch, relocation and charging of electric taxis. To evaluate the performance of our algorithms, we designed a discrete-event simulator. The application models a taxi fleet and computes relative performance according to average waiting time and hourly income per taxi. We show that dispatching taxis based on the solution to an assignment problem can provide a 20% increase in income relative to the simplistic approach where requests are assigned to the nearest taxi. Furthermore, we adapt to the case of taxi fleet management a relocation strategy designed for ambulances. Finally, in order to efficiently manage battery charges, we use a strategy that involves terminal calls. This strategy stabilizes the average state of charge and eases operations overall.

运输领域中新技术的出现导致了新的商业模式的建立，这些商业模式得益于其功能。其中，Taxelco项目Teo Taxi使用独特的商业模式：出租车司机是雇员，而不是自雇人士。此外，该公司仅使用电动汽车。这种转变给车队管理和流程优化带来了新的挑战。本文解决了这些问题，并提出了针对三个运营问题的解决方案：电动出租车的调度，迁移和充电。为了评估算法的性能，我们设计了一个离散事件模拟器。该应用程序对出租车队进行建模，并根据平均等待时间和每辆出租车的每小时收入来计算相对性能。我们表明，基于分配问题的解决方案来调度出租车，相对于将请求分配给最近的出租车的简单方法而言，可以增加20％的收入。此外，我们针对出租车车队管理的情况进行了调整，该策略是为救护车设计的。最后，为了有效地管理电池电量，我们使用了涉及终端呼叫的策略。此策略可稳定平均充电状态并简化总体操作。