We study fair resource allocation under a connectedness constraint wherein a set of indivisible items are arranged on a path and only connected subsets of items may be allocated to the agents. An allocation is deemed fair if it satisfies equitability up to one good (EQ1), which requires that agents' utilities are approximately equal. We show that achieving EQ1 in conjunction with well-studied measures of economic efficiency (such as Pareto optimality, non-wastefulness, maximum egalitarian or utilitarian welfare) is computationally hard even for binary additive valuations. On the algorithmic side, we show that by relaxing the efficiency requirement, a connected EQ1 allocation can be computed in polynomial time for any given ordering of agents, even for general monotone valuations. Interestingly, the allocation computed by our algorithm has the highest egalitarian welfare among all allocations consistent with the given ordering. On the other hand, if efficiency is required, then tractability can still be achieved for binary additive valuations with interval structure. On our way, we strengthen some of the existing results in the literature for other fairness notions such as envy-freeness up to one good (EF1), and also provide novel results for negatively-valued items or chores.
翻译:我们根据关联性限制研究公平资源分配问题,在这种限制下,将一组不可分割的项目安排在一条路径上,并且只能向代理商分配一些相联的物品。如果分配符合最高一个商品(EQ1)的公平性(EQ1),即要求代理商的公用事业大致相等。我们表明,实现EQ1,加上经过认真研究的经济效率措施(如Pareto最佳性、非浪费性、最大平等性或实用性福利),即使对于二进制添加剂的估价来说,也是很难计算出来的。在算法方面,我们通过放松效率要求,可以对任何特定代理人的订单,甚至对于一般单调价的估价,在多价时间内计算相关的EQ1分配。有趣的是,我们算算算的所有分配在与给定的顺序一致的所有分配中,具有最高的平等福利。另一方面,如果需要效率,那么对于带有间隙结构的二进制添加剂估价,那么仍然可以实现牵引力。在我们的方法上,我们加强现有的文献中的一些结果,用于其他公平概念,例如无嫉妒性或新作好的工作(EF1),也从负价值的物品。