论文标题
在线乘车系统的多目标优化框架
A multi-objective optimization framework for on-line ridesharing systems
论文作者
论文摘要
乘车系统的最终目标是与那些没有车辆与那些旅行者共享车辆的车辆的匹配者。在具有类似行程和时间表的Thhose中可以找到一个很好的比赛。在这一过程中，每个骑手都可以毫不拖延地送达，而且每个驾驶员也可以尽可能多地赚钱，而不会从其原始路线中进行过多的驱动。我们提出了一种算法利用基于生物地理学的优化，以解决在线乘车共享的多目标优化问题。必须将乘车问题作为多目标问题解决乘车问题，因为必须同时同时考虑一些重要的目标。我们通过在北京乘车共享数据集上评估实践来测试算法。仿真结果表明，BBO为最先进的拼接优化算法提供了竞争性的性能。
The ultimate goal of ridesharing systems is to matchtravelers who do not have a vehicle with those travelers whowant to share their vehicle. A good match can be found amongthose who have similar itineraries and time schedules. In thisway each rider can be served without any delay and also eachdriver can earn as much as possible without having too muchdeviation from their original route. We propose an algorithmthat leverages biogeography-based optimization to solve a multi-objective optimization problem for online ridesharing. It isnecessary to solve the ridesharing problem as a multi-objectiveproblem since there are some important objectives that must beconsidered simultaneously. We test our algorithm by evaluatingperformance on the Beijing ridesharing dataset. The simulationresults indicate that BBO provides competitive performancerelative to state-of-the-art ridesharing optimization algorithms.
