.png){kind=icon}
.png){kind=icon}
Return
Γ-robust linear complementarity problems with ellipsoidal uncertainty sets
.png){kind=icon}
OA
AI
DOI：10.1111/itor.12988.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
We study uncertain linear complementarity problems (LCPs), that is, problems in which the LCP vector q or the LCP matrix M may contain uncertain parameters. To this end, we use the concept of Gamma-robust optimization applied to the gap function formulation of the LCP. Thus, this work builds upon Krebs and Schmidt (2020). There, we studied Gamma-robustified LCPs for l(1)- and box-uncertainty sets, whereas we now focus on ellipsoidal uncertainty sets. For uncertainty in q or M, we derive conditions for the tractability of the robust counterparts. For these counterparts, we also give conditions for the existence and uniqueness of their solutions. Finally, a case study for the uncertain traffic equilibrium problem is considered, which illustrates the effects of the values of Gamma on the feasibility and quality of the respective robustified solutions.
Keywords:
robust optimization
linear complementarity problems
ellipsoidal uncertainty sets
traffic equilibrium problems
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
2.9
Papers:
1.8K
Citations:
3.7K