Recent research found that fairness plays a key role in customer satisfaction. Therefore, many manufacturing and services industries have become aware of the need to treat customers fairly. Still, there is a huge lack of models that enable industries to make operational decisions fairly, such as a fair scheduling of the customers' jobs. Our main aim in this research is to provide a unified framework to enable schedulers making fair decisions in repetitive scheduling environments. For doing so, we consider a set of repetitive scheduling problems involving a set of $n$ clients. In each out of $q$ consecutive operational periods (e.g. days), each one of the customers submits a job for processing by an operational system. The scheduler's aim is to provide a schedule for each of the $q$ periods such that the quality of service (QoS) received by each of the clients will meet a certain predefined threshold. The QoS of a client may take several different forms, e.g., the number of days that the customer receives its job later than a given due-date, the number of times the customer receive his preferred time slot for service, or the sum of waiting times for service. We analyze the single machine variant of the problem for several different definitions of QoS, and classify the complexity of the corresponding problems using the theories of classical and parameterized complexity. We also study the price of fairness, i.e., the loss in the system's efficiency that results from the need to provide fair solutions.

翻译：近期研究发现，公平性在客户满意度中扮演关键角色。因此，许多制造与服务业已认识到公平对待客户的必要性。然而，目前仍缺乏能够帮助行业做出公平运营决策的模型，例如对客户作业进行公平调度。本研究的主要目标是建立一个统一框架，使调度员能够在重复调度环境中做出公平决策。为此，我们考虑一组涉及$n$个客户的重复调度问题。在连续$q$个运营周期（如天数）的每个周期中，每位客户提交一个作业供运营系统处理。调度员的目标是为每个周期制定调度方案，使得每位客户获得的服务质量（QoS）满足预设阈值。客户的QoS可采取多种形式，例如客户在其截止日期后获得作业的天数、客户获得其首选服务时段次数、或服务等待时间总和。我们针对单机变体问题，基于多种QoS定义进行分析，并运用经典复杂度理论与参数化复杂度理论对相应问题的复杂度进行分类。此外，我们还研究了公平性的代价，即因需要提供公平解决方案而导致的系统效率损失。