Improvements to Worker Assignment in Bike Sharing Systems
Improvements to Worker Assignment in Bike Sharing Systems
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DOI：
10.1109/mass52906.2021.00092
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发表时间：
2021-10
期刊：
影响因子：
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通讯作者：
Trent Johnson;Jie Wu
中科院分区：
文献类型：
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作者：
Trent Johnson;Jie Wu
自行车共享系统（BSS）在世界各地的城市中广泛使用，因为它们提供了一种经济实惠，环保的交通方式。然而，从车站租用和归还自行车的比率并不总是相等的。需求不平衡的车站可以通过将所有码头填满或清空而停止服务。这些停止服务的电台可能会导致更差的用户体验和更少的人使用BSS。研究人员正试图通过开发算法来解决再平衡问题，激励工人从不同的站点取放自行车，以平衡租金和回报率。这些算法中的许多算法专注于创建激励和定价模型，以鼓励工人前往不平衡的车站。由于他们没有考虑所有的工人的安置，这种策略可能会导致效率低下，工人旅行比他们需要的更远。我们可以将重新平衡视为工作分配问题，通过分配工作站来最小化总行驶距离。我们提出了一种算法，可以近似的最优分配显着快于其他技术具有非常高的性能。快速的速度允许在增强定价模型中实时使用，并作为工人分配的独立方法。此外，我们将我们的方法与四种现有的算法在现实世界的数据进行比较，以评估计算速度和有效性。
Bike-sharing systems (BSSs) are widely used in cities worldwide as they offer an affordable, eco-friendly method of transport. However, the rate of renting and returning bikes from stations is not always equal. The stations with imbalanced demand can become out of service by having all docks filled or emptied. These out-of-service stations can lead to a worse user experience and fewer people using BSSs. Researchers are trying to solve the rebalancing problem by developing algorithms that incentivize workers to pick up and drop off bicycles from different stations to balance the rent and return rates. Many of these algorithms focus on creating incentive and pricing models to encourage workers to go to imbalanced stations. Since they do not consider all of the placements of workers, this strategy may lead to inefficiencies where workers travel farther than they need. We can treat rebalancing as a Worker Assignment Problem by assigning worker stations to minimize the total distance traveled. We propose an algorithm that can approximate the optimal assignment significantly faster than other techniques with very high performance. The rapid speed allows for real-time use in augmenting pricing models and as a stand-alone method for worker assignment. Furthermore, we compare our approach against four existing algorithms on real-world data to evaluate computational speed and effectiveness.