For many real-world decision-making problems subject to uncertainty, it may be essential to deal with multiple and often conflicting objectives while taking the decision-makers' risk preferences into account. Conditional value-at-risk (CVaR) is a widely applied risk measure to address risk-averseness of the decision-makers. In this paper, we use the subset-based polyhedral representation of the CVaR to reformulate the bi-objective two-stage stochastic facility location problem presented in Nazemi et al. (2021). We propose an approximate cutting-plane method to deal with this more computationally challenging subset-based formulation. Then, the cutting plane method is embedded into the epsilon-constraint method, the balanced-box method, and a recently developed matheuristic method to address the bi-objective nature of the problem. Our computational results show the effectiveness of the proposed method. Finally, we discuss how incorporating an approximation of the subset-based polyhedral formulation affects the obtained solutions.
翻译:对于面临不确定性的许多现实世界决策问题,在考虑决策者的风险偏好时,必须处理许多往往相互矛盾的多重目标。有条件值风险(CVaR)是广泛应用的风险评估措施,旨在解决决策者对风险的厌恶。在本文中,我们使用基于子集的CVaR多元代表制重塑Nazemi等人(2021年)提出的双目标两阶段随机设施定位问题。我们提议了一种大致的切割机方法,以应对这一更具计算难度的子集成配方。然后,切割机方法嵌入了易碎石-分层法、平衡箱法和最近开发的一种数学方法,以解决问题的双目标性质。我们的计算结果显示了拟议方法的有效性。最后,我们讨论了如何将子集成的组合组合组合组合组合组合组合组合组合组合组合的近似近影响获得的解决办法。