论文标题
在优化模型中平衡公平和效率
Balancing Fairness and Efficiency in an Optimization Model
论文作者
论文摘要
优化模型通常是通过最大化总收益或最小化成本来实现效率的目标。然而，公平与效率之间的权衡是许多实际决策的重要组成部分。我们提出了一种在优化模型中平衡这两个标准的原则且实用的方法。在对现有方案进行了批判性评估之后，我们定义了一组社会福利功能（SWF），它们结合了Rawlsian Leximax公平和功利主义，并克服了以前方法的某些弱点。特别是，我们通过在实际情况下具有有意义的解释的单个参数来规范权益/效率权衡。我们使用混合整数约束来制定SWF，并依次最大化它们受到指定问题的约束。在提供实施的实用分步说明之后，我们演示了有关涉及医疗资源分配和灾难准备的实际规模问题的方法。解决方案时间适中，范围从二秒的一小部分到定位参数的给定值。
Optimization models generally aim for efficiency by maximizing total benefit or minimizing cost. Yet a trade-off between fairness and efficiency is an important element of many practical decisions. We propose a principled and practical method for balancing these two criteria in an optimization model. Following a critical assessment of existing schemes, we define a set of social welfare functions (SWFs) that combine Rawlsian leximax fairness and utilitarianism and overcome some of the weaknesses of previous approaches. In particular, we regulate the equity/efficiency trade-off with a single parameter that has a meaningful interpretation in practical contexts. We formulate the SWFs using mixed integer constraints and sequentially maximize them subject to constraints that define the problem at hand. After providing practical step-by-step instructions for implementation, we demonstrate the method on problems of realistic size involving healthcare resource allocation and disaster preparation. The solution times are modest, ranging from a fraction of a second to 18 seconds for a given value of the trade-off parameter.
