发表机构
University of British Columbia（不列颠哥伦比亚大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出开放优化程序框架，通过变量共享定义互联，刻画开放二次程序的闭包性与适定性，分析逐模块求解的收敛性并给出误差界，为优化架构的组合设计提供途径。
AI 中文摘要
本文研究了开放优化程序，即被视为开放系统的参数优化程序及其互联。每个开放优化程序被赋予一个行为，互联通过变量共享来定义。对于一类开放二次程序（QPs），我们刻画了互联下的闭包性和适定性，并且对于通过添加目标函数而互联的模块，分析了顺序逐模块求解方法的收敛性，推导了所得近似的误差界。我们进一步说明，模块互联所通过的变量指示了适当的行为描述，并且每种描述都需要专用的互联规则。这一视角为优化架构的组合分析与设计指明了一条途径。
英文摘要
The paper studies open optimization programs, that is, parametric optimization programs viewed as open systems, and their interconnection. Each open optimization program is assigned a behavior and interconnection is defined through variable sharing. For a class of open quadratic programs (QPs), we characterize closure and well-posedness under interconnection and, for modules interconnected by adding their objectives, analyze the convergence of a sequential module-by-module solution method, deriving error bounds for the resulting approximation. We further illustrate that the variables through which modules are interconnected indicate an appropriate behavioral description, and each description requires dedicated interconnection rules. This perspective suggests a route toward compositional analysis and design of optimization architectures.
CommentsTo appear in the Proceedings of the 65th IEEE Conference on Decision and Control (CDC 2026)
