Year: 2024
Type: article
Abstract: This paper explores the integration of Conditional Value-at-Risk (CVaR) into the field of Multi-Objective Optimization (MOO), offering insights into its mathematical basis, significance in risk assessment, and application in complex decision-making scenarios. It discusses the challenges of MOO, presents traditional solution methods, and examines the advantages and limitations of CVaR. The article highlights the flexibility of CVaR as an objective function, particularly in financial portfolio optimization, and discusses future research directions for enhancing its computational techniques, expanding application areas, and improving responsiveness to real-world dynamics.
DOI: 10.62051/hb75mv91
Author: Juandan Luo
Institution: Shanghai Jiao Tong University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4402937221