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math.OC2026

Deep FlexQP: Accelerated Nonlinear Programming via Deep Unfolding

Alex Oshin, Rahul Vodeb Ghosh, Augustinos D. Saravanos +1

We propose FlexQP, an always-feasible convex quadratic programming (QP) solver based on an elastic relaxation of the QP constraints. If the original constraints are feasib…

math.OC2026

Second-Order Constrained Dynamic Optimization

Yuichiro Aoyama, Oswin So, Augustinos D. Saravanos +1

This paper provides an overview, analysis, and comparison of second-order dynamic optimization algorithms, i.e., constrained Differential Dynamic Programming (DDP) and Sequential Q…

math.OC2025

Distributed Stochastic Search for Multi-Agent Model Predictive Control

Taehyun Yoon, Augustinos D. Saravanos, Evangelos A. Theodorou

Many real-world multi-agent systems exhibit nonlinear dynamics and complex inter-agent interactions. As these systems increase in scale, the main challenges arise from achieving sc…

math.OC2025

Scaling Robust Optimization for Swarms: A Distributed Perspective

Arshiya Taj Abdul, Augustinos D. Saravanos, Evangelos A. Theodorou

This article introduces a decentralized robust optimization framework for safe multi-agent control under uncertainty. Although stochastic noise has been the primary form of modelin…

math.OC2025

Deep Distributed Optimization for Large-Scale Quadratic Programming

Augustinos D. Saravanos, Hunter Kuperman, Alex Oshin +3

Quadratic programming (QP) forms a crucial foundation in optimization, encompassing a broad spectrum of domains and serving as the basis for more advanced algorithms. Consequently,…