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arXiv 2409.08993cs.GT
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用于扩展设施可达性的机制设计

Mechanism Design for Extending the Accessibility of Facilities

Hau Chan, Jianan Lin, Chenhao Wang, Yanxi Xie

AI总结:

该研究针对设施位置固定的无金钱机制设计场景,提出构建带接驳服务的可达范围以提升设施可达性,设计了针对社会成本与最大成本目标的、具有渐近紧近似比的群体防策略操纵机制。

摘要:

我们在无金钱机制设计的背景下,研究了一类旨在提升智能体对设施可达性的设施选址问题(FLPs)变体。在该变体中,智能体对实数轴上的设施理想位置有各自偏好,且设施位置是预先固定的——由于各类约束(例如空间有限、建设成本问题),无法对设施进行(重新)选址。为提升智能体对设施的可达性,现有FLP机制设计文献提出了两种思路:一是对实数轴进行结构修改(例如新增一个区间),二是在无法进行结构修改时在两点之间提供接驳服务。本文聚焦于第二种思路,提出构建可达范围以扩展设施的可达性。在该范围内,智能体可获得适配服务(例如校车、校园接驳车或接送服务)以抵达设施。因此,每个智能体的成本为其理想位置通过该可达范围到设施的(可行)距离。我们专注于设计策略-proof(防策略操纵)机制,这类机制能引导智能体上报真实的理想位置,并构建可达范围(区间)以近似最小化社会成本或智能体的最大成本。针对社会成本和最大成本两类目标,我们分别设计了具有渐近紧近似比界的群体防策略操纵机制。

英文摘要:

We study a variation of facility location problems (FLPs) that aims to improve the accessibility of agents to the facility within the context of mechanism design without money. In such a variation, agents have preferences on the ideal locations of the facility on a real line, and the facility's location is fixed in advance where (re)locating the facility is not possible due to various constraints (e.g., limited space and construction costs). To improve the accessibility of agents to facilities, existing mechanism design literature in FLPs has proposed to structurally modify the real line (e.g., by adding a new interval) or provide shuttle services between two points when structural modifications are not possible. In this paper, we focus on the latter approach and propose to construct an accessibility range to extend the accessibility of the facility. In the range, agents can receive accommodations (e.g., school buses, campus shuttles, or pickup services) to help reach the facility. Therefore, the cost of each agent is the distance from their ideal location to the facility (possibility) through the range. We focus on designing strategyproof mechanisms that elicit true ideal locations from the agents and construct accessibility ranges (intervals) to approximately minimize the social cost or the maximum cost of agents. For both social and maximum costs, we design group strategyproof mechanisms with asymptotically tight bounds on the approximation ratios.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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