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Approximation Algorithms for a Location-Based Group Gathering Service with Multiple Roles

机译:具有多个角色的基于位置的组收集服务的近似算法

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We study the problem of a location-based group gathering service (LGS) with the objective of minimizing the time for agents such as people or robots to meet in a two-dimensional space. A need for LGS occurs in many situations such as soldier rescue in battle fields, family gathering at a parking lot, airport shuttle(s) pick-up and drop off of people, and robot cooperation. We consider two agent roles: receivers and providers. Receivers (e.g. elderly, disabled, wounded) cannot move to the final location until they are "picked up" by providers. We name this problem location-based group gathering service with provider-receiver constraint (LGS-PRC). We formulate LGS-PRC and prove it is NP-complete. Accordingly, we provide an approximation algorithm, Partition-Assignment Gathering (PAG), and prove it achieves a constant approximation ratio compared to the lower bound. Numerical results show PAG is within the approximation ratio, and that it outperforms the algorithm that assigns the closest provider to a receiver.
机译:我们研究了基于位置的群体聚集服务(LGS)的问题,目的是最大限度地减少人们或机器人的代理时间,以便在二维空间中满足。在战斗领域的士兵救援等许多情况下,在战斗领域,家庭聚集在停车场,机场班车接送和下降人员,以及机器人合作,以及机器人合作的许多情况下发生了许多情况。我们考虑两个代理角色:接收者和提供者。接收器(例如老年人,残疾人,受伤)不能转移到最终位置,直到供应商“拿起”。我们将基于问题的基于位置的群组收集服务命名为Provider-Receiver约束(LGS-PRC)。我们制定LGS-PRC并证明它是NP完整的。因此,我们提供了一种近似算法,分配 - 分配收集(PAG),并证明它与下限相比达到恒定近似比。数值结果显示PAG在近似值范围内,并且它优于将最接近提供商分配给接收器的算法。

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