The price of anarchy in loss systems
研究了多服务器无记忆损失系统中，社会最优与纳什均衡下顾客期望收益之比（无政府代价）的上界，并证明该上界对任意服务器数量都是紧的。
Abstract Assume a multi‐server memoryless loss system. Each server is associated with a service rate and a value of service. Customers from a common Poisson arrival process are routed to the servers in an unobservable way, where the goal is to maximize the long‐run expected reward per customer (which is the service value times the probability that the customer is not blocked). We first solve this problem under two criteria: social optimization and Nash equilibrium. Our main result is that the price of anarchy, defined as the ratio between the expected gain under the two criteria, is bounded by . We also show, via examples, that this bound is tight for any number of servers.