5 papers
Fragility of Minimum-Variance Portfolios
Daniel Ovalle, Carl D. Laird, Ignacio E. Grossmann +1
Minimum-variance portfolios are well known to be highly sensitive to covariance estimation error. In this paper, we show that by imposing a block diagonal correlation structure, we…
Efficient Convexification of Kolmogorov-Arnold Networks with Polynomial Functional Forms Via a Continuous Graham Scan Approach
Tianwei Li, Daniel Ovalle, Barnabas Poczos +3
Deterministic global optimization of nonlinear models is important in many scientific and engineering applications. This framework typically involves repeatedly solving convex rela…
Conformal Mixed-Integer Constraint Learning with Feasibility Guarantees
Daniel Ovalle, Lorenz T. Biegler, Ignacio E. Grossmann +2
We propose Conformal Mixed-Integer Constraint Learning (C-MICL), a novel framework that provides probabilistic feasibility guarantees for data-driven constraints in optimization pr…
Event Constrained Programming
Daniel Ovalle, Stefan Mazzadi, Carl D. Laird +2
In this paper, we present event constraints as a new modeling paradigm that generalizes joint chance constraints from stochastic optimization to (1) enforce a constraint on the pro…
Optimal Reactive Operation of General Topology Supply Chain and Manufacturing Networks under Disruptions
Daniel Ovalle, Joshua L. Pulsipher, Yixin Ye +4
Supply and manufacturing networks in the chemical industry involve diverse processing steps across different locations, rendering their operation vulnerable to disruptions from unp…