论文标题
在完整偏好域上的限制序列规则
Constrained Serial Rule on the Full Preference Domain
论文作者
论文摘要
我们研究在对象之间允许对象无关紧要时，在存在任意线性约束的情况下将对象分配给代理的问题。我们的主要贡献是通过称为约束序列规则的新机制对（扩展）概率序列机制的概括。该机制在计算上是有效的，并且保持了理想的效率和公平性能，即同一类型的药物之间的限制顺序效率和嫉妒性。我们的机制基于一种线性编程方法，该方法解释了所有约束，并重新解释了构成扩展概率序列机制至关重要部分的瓶颈集合集。
We study the problem of assigning objects to agents in the presence of arbitrary linear constraints when agents are allowed to be indifferent between objects. Our main contribution is the generalization of the (Extended) Probabilistic Serial mechanism via a new mechanism called the Constrained Serial Rule. This mechanism is computationally efficient and maintains desirable efficiency and fairness properties namely constrained ordinal efficiency and envy-freeness among agents of the same type. Our mechanism is based on a linear programming approach that accounts for all constraints and provides a re-interpretation of the bottleneck set of agents that form a crucial part of the Extended Probabilistic Serial mechanism.
