Maximizing utilitarian and Egalitarian welfare of fractional hedonic games on tree-like graphs

IF 1.1 4区 数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Combinatorial Optimization Pub Date : 2025-04-14 DOI:10.1007/s10878-025-01283-6
Tesshu Hanaka, Airi Ikeyama, Hirotaka Ono
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Abstract

Fractional hedonic games are coalition formation games where a player’s utility is determined by the average value they assign to the members of their coalition. These games are a variation of graph hedonic games, which are a class of coalition formation games that can be succinctly represented. Due to their applicability in network clustering and their relationship to graph hedonic games, fractional hedonic games have been extensively studied from various perspectives. However, finding welfare-maximizing partitions in fractional hedonic games is a challenging task due to the nonlinearity of utilities. In fact, it has been proven to be NP-hard and can be solved in polynomial time only for a limited number of graph classes, such as trees. This paper presents (pseudo)polynomial-time algorithms to compute welfare-maximizing partitions in fractional hedonic games on tree-like graphs. We consider two types of social welfare measures: utilitarian and egalitarian. Tree-like graphs refer to graphs with bounded treewidth and block graphs. A hardness result is provided, demonstrating that the pseudopolynomial-time solvability is the best possible under the assumption P \(\ne \) NP.

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树状图上分数享乐博弈的功利与平等福利最大化
分数享乐游戏是指联盟形成游戏,其中玩家的效用取决于他们分配给联盟成员的平均值。这些游戏是图享乐游戏的变体,图享乐游戏是一类可以简洁地表示的联盟形成游戏。由于分数型快乐对策在网络聚类中的适用性以及与图享乐对策的关系,分数型快乐对策从各个角度得到了广泛的研究。然而,由于效用的非线性,在分数享乐博弈中寻找福利最大化分区是一项具有挑战性的任务。事实上,它已经被证明是np困难的,并且只能在多项式时间内解决有限数量的图类,例如树。本文提出了计算树状图上分数阶享乐对策中福利最大化分区的(伪)多项式时间算法。我们考虑两种类型的社会福利措施:功利主义和平等主义。树形图是指具有有限树宽的图和块图。给出了一个硬度结果,证明了在P \(\ne \) NP假设下伪多项式时间可解性是最好的。
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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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