不同偏好的离散设施定位游戏

IF 0.9 4区 数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Combinatorial Optimization Pub Date : 2023-09-13 DOI:10.1007/s10878-023-01082-x
Ling Gai, Mengpei Liang, Chenhao Wang
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引用次数: 0

摘要

我们研究了具有不同偏好的离散设施位置游戏的机制设计,其中设施只能在有限的候选位置集合中建造,并且机制将代理位置映射到建造设施的候选位置。我们既考虑了令人讨厌的偏好,即代理人希望尽可能远离设施,也考虑了双重偏好,即每个代理人可能喜欢或不喜欢一个设施。当偏好令人讨厌时,对于两个异质设施,我们提出了一个群体策略证明机制,该机制对社会效用目标和最小效用目标的近似比均为2。两个目标都被证明具有\(\frac{3}{2}\)的下界。对于两个齐次设施,我们证明了不存在具有有界逼近比的确定策略证明机制。当偏好是双重的时,我们考虑了社会效用目标下的单设施位置博弈,并提出了一种近似率为4的群体策略证明机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Discrete facility location games with different preferences

We study the mechanism design for discrete facility location games with different preferences, where the facilities can only be built at a finite set of candidate locations, and a mechanism maps the agent locations to candidate locations for building facilities. We consider both the obnoxious preferences, where the agents want to stay as far away as possible from the facilities, and the dual preferences, where each agent may either like or dislike a facility. When the preferences are obnoxious, for two heterogeneous facilities, we present a group strategy-proof mechanism which has an approximation ratio of 2 for both social utility objective and minimum utility objective. Both objectives are proven to have a lower bound of \(\frac{3}{2}\). For two homogeneous facilities, we prove there is no deterministic strategy-proof mechanism with bounded approximation ratio. When the preferences are dual, we consider the single facility location games under the social utility objective, and propose a group strategy-proof mechanism with approximation ratio of 4.

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来源期刊
Journal of Combinatorial Optimization
Journal of Combinatorial Optimization 数学-计算机:跨学科应用
CiteScore
2.00
自引率
10.00%
发文量
83
审稿时长
6 months
期刊介绍: The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering. The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.
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