Becker, YannickYannickBeckerHalffmann, PascalPascalHalffmannSchöbel, AnitaAnitaSchöbel2025-08-262025-08-262025https://publica.fraunhofer.de/handle/publica/49456710.1007/978-3-031-92575-7_22In portfolio optimization, decision makers face difficulties from uncertainties inherent in real-world scenarios. These uncertainties significantly influence portfolio outcomes in both classical and multi-objective Markowitz models. To address these challenges, our research explores the power of robust multi-objective optimization. Since portfolio managers frequently measure their solutions against benchmarks, we enhance the multi-objective min-regret robustness concept by incorporating these benchmark comparisons. This approach bridges the gap between theoretical models and real-world investment scenarios, offering portfolio managers more reliable and adaptable strategies for navigating market uncertainties. Our framework provides a more nuanced and practical approach to portfolio optimization under real-world conditions.enRisk Management in Multi-objective Portfolio Optimization Under Uncertaintyconference paper