We study the problem of fairly allocating a set of indivisible goods among agents with matroid rank valuations. We present a simple framework that efficiently computes any fairness objective that satisfies some mild assumptions. Along with maximizing a fairness objective, the framework is guaranteed to run in polynomial time, maximize utilitarian social welfare and ensure strategyproofness. We show how our framework can be used to achieve four different fairness objectives: (a) Prioritized Lorenz dominance, (b) Maxmin fairness, (c) Weighted leximin, and (d) Max weighted Nash welfare. In particular, our framework provides the first polynomial time algorithms to compute weighted leximin and max weighted Nash welfare allocations for matroid rank valuations.
翻译:我们研究的是在具有类固醇等级估价的代理人之间公平分配一组不可分割货物的问题。我们提出了一个简单的框架,有效地计算任何符合某些轻度假设的公平目标。除了实现一个公平目标之外,这个框架还保证在多元制时间运行,尽量扩大功利主义的社会福利和确保战略的可靠性。我们展示了如何利用我们的框架来实现四个不同的公平目标:(a) 优先的洛伦茨支配地位,(b) 最起码的公平性,(c) 加权的纳什明,以及(d) 加权的马克斯纳什福利。特别是,我们的框架提供了第一个计算加权地契和最高加权的纳什福利分配的混合时间算法,用于计算按类固醇等级估价的加权地产和最高加权的纳什福利分配。