We consider non-cooperative facility location games where both facilities and clients act strategically and heavily influence each other. This contrasts established game-theoretic facility location models with non-strategic clients that simply select the closest opened facility. In our model, every facility location has a set of attracted clients and each client has a set of shopping locations and a weight that corresponds to her spending capacity. Facility agents selfishly select a location for opening their facility to maximize the attracted total spending capacity, whereas clients strategically decide how to distribute their spending capacity among the opened facilities in their shopping range. We focus on a natural client behavior similar to classical load balancing: our selfish clients aim for a distribution that minimizes their maximum waiting times for getting serviced, where a facility's waiting time corresponds to its total attracted client weight. We show that subgame perfect equilibria exist and give almost tight constant bounds on the Price of Anarchy and the Price of Stability, which even hold for a broader class of games with arbitrary client behavior. Since facilities and clients influence each other, it is crucial for the facilities to anticipate the selfish clients' behavior when selecting their location. For this, we provide an efficient algorithm that also implies an efficient check for equilibrium. Finally, we show that computing a socially optimal facility placement is NP-hard and that this result holds for all feasible client weight distributions.
翻译:我们考虑的是非合作设施定位游戏,其中设施和客户都从战略角度采取行动,相互产生严重影响。这与既定的游戏理论设施定位模式形成对比,而非战略客户只是选择最接近的开放设施。在我们的模式中,每个设施地点都有一套吸引的客户,每个客户都有一套购物地点和与其支出能力相当的重量。设施代理商自私地选择一个开放设施的地点,以最大限度地扩大吸引的全部支出能力,而客户则从战略上决定如何在开放设施中分配支出能力,而客户则从战略上决定如何在其购物范围中将自己的支出能力分配到不同的采购范围。我们注重的是类似于传统负荷平衡的自然客户行为:我们的自私客户的目标是让分配尽可能减少其最大的等待时间,使设施等待的时间与吸引的客户总重量相符。我们展示的是,每个设施都有一套完美的静态和稳定价格的子游戏,甚至能维持更大规模的游戏,而设施和客户相互影响,因此对于设施在选择其位置时预测自私的客户行为至关重要。为此,我们提供了一种高效的、最合理的计算方法,我们最终会显示一个高效的客户配置。