发表机构
Ocean University of China（中国海洋大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究具有可选偏好的桥梁选址问题，设计策略证明机制，分别针对社会成本和最大成本目标给出最优或近似机制及下界。
AI 中文摘要
我们研究了具有可选偏好的桥梁选址问题，其中两个分离的区域各包含一个预先定位的设施。每个智能体拥有一个私人位置和一个私人偏好，该偏好指定了她感兴趣的两个设施中的一个非空子集。她的个人成本通过三种自然变体之一来衡量：她到感兴趣设施距离的最大值、总和或最小值。社会规划者必须设计确定性的策略证明机制，以引出真实报告，选择连接桥梁的位置，并近似最小化社会成本或最大成本。我们的主要结果如下。对于社会成本目标，我们为最大变体和总和变体成本设计了最优机制，为最小变体成本提供了3近似机制，并建立了最小变体的2下界。对于最大成本目标，我们为最大变体和总和变体成本提供了5/3近似机制，为最小变体成本提供了3近似机制；我们还证明了在最大成本目标下适用于所有三种成本变体的共同下界5/3。
英文摘要
We study the bridge location problem with optional preferences, where two separated regions each contain one prelocated facility. Each agent has a private location and a private preference specifying a nonempty subset of the two facilities in which she is interested. Her individual cost is measured by one of three natural variants: the maximum, the sum, or the minimum of her distances to the facilities in which she is interested. The social planner must design deterministic strategyproof mechanisms that elicit truthful reports, choose the location of a connecting bridge, and approximately minimize either the social cost or the maximum cost. Our main results are as follows. For the social cost objective, we design optimal mechanisms for the max-variant and sum-variant costs, and provide a 3-approximation mechanism for the min-variant cost, and establish a lower bound of 2 for the min-variant. For the maximum cost objective, we give 5/3-approximation mechanisms for the max-variant and sum-variant costs, and a 3-approximation mechanism for the min-variant cost; we also prove a common lower bound of 5/3 that applies to all three cost variants under the maximum cost objective.
CommentsTAMC 2026
