math.OC · 2026-09-22 · No. 121

Optimization and Control, 2026-09-22.

2 new papers in math.OC. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

2 entries
  1. 01

    Reinforcement Learning in Operational Research: A Technical Review and Practical Roadmap

    Yahan Lu, Dongyang Xia, Nursen Aydin, Shadi Sharif Azadeh

    math.OC · cs.LG

    The growing demand for real-time, data-driven decision-making in complex and dynamic systems is placing increasing pressure on traditional Operational Research (OR) methodologies. Reinforcement learning (RL) has emerged as a complementary approach, offering strong learning and computational capabilities for sequential decision-making in dynamic and uncertain environments. Recent research shows an increasing interest in integrating RL with OR...

    arxiv.org/abs/2609.24750 · PDF

  2. 02

    Complexities of Weak Proximal Oracle Methods for Composite Convex Optimization

    Dan Garber

    math.OC · cs.LG

    We consider a standard convex composite optimization problem with either smooth or nonsmooth objective function, and under quadratic growth. In recent years, several works gave algorithms based on a \textit{weak proximal oracle} (WPO) that essentially match in oracle complexities proximal (sub)gradient methods relying on exact prox operations. Importantly, such WPOs, which relax the strong optimality condition of the standard prox operator,...

    arxiv.org/abs/2609.24423 · PDF

This edition is part of The Daily Abstract — math.OC archive. Subscribe to receive these in your inbox each morning, automatically translated to Spanish, with reply-to-PDF: arxivdaily.ignorelist.com.

Colophon Set in Georgia, with system sans for interface chrome and a monospaced stack for code and paper identifiers. Sole accent: amber #D99C5E. Built and served on an always-free VM. The masthead is set 14% letterspaced because newspapers do that and it works.