Equitable allocations in risk-averse settings

Abstract Many real life problems require making decisions that lead to benefit allocations across multiple entities, hence they can be cast as special types of multiobjective programming problems. In such settings, the decision makers often have fairness concerns alongside efficiency concerns. We propose a method for achieving equitable and efficient solutions for these multicriteria problems in the context of risk-averse behavior when the benefits are uncertain. To accomplish this, we introduce a methodology that combines two distinct concepts: Conditional Value-at-Risk (CVaR) and equitable aggregations. By integrating these two concepts, we aim to establish a framework for equitable, risk-aware decision-making and address the important challenge of ensuring fairness in an uncertain environment.