An Effective Fleet Management Strategy for Collaborative Spatio-Temporal Searching: GIS Cup

Lingfeng Ming, Q. Hu, Ming Dong, Bolong Zheng
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引用次数: 7

Abstract

The ACM SIGSPATIAL GIS Cup 2020 focuses on the Collaborative Spatio-Temporal Searching (CSTS) problem, in which a fleet of mobile agents search for stationary resources on a road network. While each resource can be obtained by exactly one agent, agents can collaborate to obtain resources as quickly as possible. The key of solving CSTS is to guide agents to "hotspot" areas and to avoid the competition by considering agent collaboration. We propose a fleet management method by formulating CSTS as a minimum cost flow problem, called MCF-FM. In addition, we develop a continuous order dispatch strategy. Our submission is the top performer in the agent utilization scenario and runner-up in the customer experience scenario. Our source code is available at: https://github.com/Chriszblong/MCF-FM.
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一种有效的协同时空搜索车队管理策略:GIS杯
ACM SIGSPATIAL GIS杯2020关注的是协同时空搜索(CSTS)问题,其中一组移动代理搜索道路网络上的固定资源。虽然每个资源只能由一个代理获得,但代理可以协作以尽可能快地获得资源。解决CSTS问题的关键在于引导agent进入“热点”区域,并通过考虑agent协作来避免竞争。我们提出了一种车队管理方法,将CSTS表述为最小成本流问题,称为MCF-FM。此外,我们制定了一个持续的订单调度策略。我们的提交在座席利用率场景中表现最好,在客户体验场景中表现第二。我们的源代码可从https://github.com/Chriszblong/MCF-FM获得。
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