This paper is part of an ongoing endeavor to bring the theory of fair division closer to practice by handling requirements from real-life applications. We focus on two requirements originating from the division of land estates: (1) each agent should receive a plot of a usable geometric shape, and (2) plots of different agents must be physically separated. With these requirements, the classic fairness notion of \emph{proportionality} is impractical, since it may be impossible to attain any multiplicative approximation of it. In contrast, the \emph{ordinal maximin share approximation}, introduced by Budish in 2011, provides meaningful fairness guarantees. We prove upper and lower bounds on achievable maximin share guarantees when the usable shapes are squares, fat rectangles, or arbitrary axis-aligned rectangles, and explore the algorithmic and query complexity of finding fair partitions in this setting. Our work makes use of tools and concepts from computational geometry such as independent sets of rectangles and guillotine partitions.
翻译:本文是一个持续的努力,旨在通过处理来自现实应用程序的要求,将公平分配理论带近到实践。 我们关注来自土地房产划分的两个要求:(1)每个参与者都应获得一个可用几何形状的地块,以及(2)不同参与者的地块必须物理上分开。由于这些要求,经典公平性概念“比例”是不切实际的,因为可能无法获得任何乘法近似值。相反,在2011年Budish引入的“序列最大化份额逼近”的概念提供了有意义的公平保证。我们证明了可实现的最大股份保证的上下界,当可用形状为正方形、肥胖矩形或任意轴对齐矩形时,以及在此设置中寻找公平分区的算法和查询复杂性。我们的工作利用了计算几何学的工具和概念,如独立的矩形集和断头台分区。