Optimization Algorithm Design via Electric Circuits

Stephen P. Boyd, Tetiana Parshakova, Ernest K. Ryu, Jaewook J. Suh
11/4/2024
math.OCcs.LG

No official code found. Best implementation: cvxgrp/optimization_via_circuits (23 stars, Apache-2.0, last commit 2026-03-10).

Abstract

We present a novel methodology for convex optimization algorithm design using ideas from electric RLC circuits. Given an optimization problem, the first stage of the methodology is to design an appropriate electric circuit whose continuous-time dynamics converge to the solution of the optimization problem at hand. Then, the second stage is an automated, computer-assisted discretization of the continuous-time dynamics, yielding a provably convergent discrete-time algorithm. Our methodology recovers many classical (distributed) optimization algorithms and enables users to quickly design and explore a wide range of new algorithms with convergence guarantees.

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Code Implementations(1)

Apache-2.0

Distributed Optimization: Analysis and Synthesis via Circuits

232Python, Jupyter NotebookNov 29, 20237 months agoApache-2.0

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Cite this paper

@article{boyd2024optimization,
  title  = {Optimization Algorithm Design via Electric Circuits},
  author = {Stephen P. Boyd and Tetiana Parshakova and Ernest K. Ryu and Jaewook J. Suh},
  year   = {2024},
  eprint = {2411.02573},
  archivePrefix = {arXiv},
  doi    = {10.48550/arXiv.2411.02573},
  url    = {http://arxiv.org/abs/2411.02573v2},
  journal = {NEURIPS 2024 2024}
}

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