Consider a population of customers each of which needs to decide independently when to arrive to a facility that provides a service during a fixed period of time, say a day. This is a common scenario in many service systems such as a bank, lunch at a cafeteria, music concert, flight check-in and many others. High demand for service at a specific time leads to congestion that comes at a cost, e.g., for waiting, earliness or tardiness. Queueing Theory provides tools for the analysis of the waiting times and associated costs. If customers have the option of deciding when to join the queue, they will face a decision dilemma of when to arrive. The level of congestion one suffers from depends on others behavior and not only that of the individual under consideration. This fact leads customers to make strategic decisions regarding their time of arrival. In addition, multiple decision makers that affect each other's expected congestion, call for non-cooperative game theoretic analysis of this strategic interaction. This common daily scenario has prompted a research stream pioneered by the ?/M/1 model of Glazer and Hassin (GH1983) that first characterized an arrival process to a queue as a Nash equilibrium solution of a game. This survey provides an overview of the main results and developments in the literature on queueing systems with strategic timing of arrivals. Another issue is that of social optimality, namely the strategy profile used by customers that optimizes their aggregate utility. In particular, we review results concerning the price of anarchy (PoA), which is the ratio between the socially optimal and the equilibrium utilities.
翻译:如果客户可以选择何时加入排队,那么他们将面临何时到达的决定困境。 拥堵程度取决于他人的行为,而不仅仅是所考虑的个人的行为。 这一事实导致客户就其抵达时间做出战略决定。 此外,影响彼此预期的拥堵的众多决策者呼吁对这一战略互动进行不合作的游戏理论分析。 这种常见的日常情景促使人们开始研究流,即Glazer和Hassin(GHA)的模型(GH1983年)之间,这是我们当前最优化的市面汇率评估,这是我们当前最优化的市面汇率评估,也是目前最优化的市面汇率评估,也是目前最优化的。