cvxRiskOpt：基于 CVXPY 的风险优化工具

IF 2.4 Q2 AUTOMATION & CONTROL SYSTEMS

IEEE Control Systems Letters Pub Date : 2024-08-30 DOI:10.1109/LCSYS.2024.3452194

Sleiman Safaoui;Tyler H. Summers

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引用次数: 0

摘要

我们介绍 cvxRiskOpt（基于风险的凸优化）：一个建立在 CVXPY 基础上的 Python 软件包，用于快速构建基于风险的凸优化问题原型，并使用 CVXPYgen 生成可嵌入的 C 代码。我们的软件包提供了高级函数来处理若干基于风险的优化问题和约束条件。这些函数将涉及随机变量和不确定性的问题和约束条件重新表述为确定性凸对应问题和约束条件。输出结果是 CVXPY 问题实例或 CVXPY 约束条件，用户可直接将其添加到 CVXPY 问题实例中。因此，我们的软件包可以使用 CVXPYgen 生成 C 代码，从而定制可嵌入的基于风险的优化问题。cvxRiskOpt 可在 https://tsummerslab.github.io/cvxRiskOpt/ 上获取。

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cvxRiskOpt: A Risk-Based Optimization Tool Based on CVXPY

We introduce cvxRiskOpt (convex Risk-based Optimization): a Python package built on top of CVXPY for the rapid prototyping of convex risk-based optimization problems and generating embeddable C code using CVXPYgen. Our package provides high-level functions to handle several risk-based optimization problems and constraints. These functions reformulate problems and constraints involving random variables and uncertainty into deterministic convex counterparts. The output is either a CVXPY Problem instance or CVXPY constraints that users can directly add to their CVXPY Problem instance. Accordingly, our package can use CVXPYgen to generate C code resulting in custom embeddable risk-based optimization problems. cvxRiskOpt is available at https://tsummerslab.github.io/cvxRiskOpt/ .

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来源期刊

IEEE Control Systems Letters Mathematics-Control and Optimization

CiteScore

4.40

自引率

13.30%

发文量

471