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Bi-objective Risk-averse Facility Location using a Subset-based Representation of the Conditional Value-at-Risk

  • Najmesadat Nazemi (Vortragende*r)
  • Parragh, S. (Vortragende*r)
  • Walter Gutjahr (Vortragende*r)

Aktivität: Vortrag oder PräsentationVortrag nach Bewerbung und AuswahlScience-to-science

Beschreibung

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 ε-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.
Zeitraum03 Feb. 2022
EreignistitelICORES 2022 - 11th International Conference on Operations Research and Enterprise Systems
VeranstaltungstypKonferenz
OrtÖsterreichAuf Karte anzeigen

Wissenschaftszweige

  • 502 Wirtschaftswissenschaften
  • 502028 Produktionswirtschaft
  • 502017 Logistik
  • 502050 Wirtschaftsinformatik
  • 101016 Optimierung
  • 502037 Standortplanung
  • 101015 Operations Research

JKU-Schwerpunkte

  • Digital Transformation
  • Sustainable Development: Responsible Technologies and Management