Optimization Algorithm Design via Electric Circuits

Stephen P. Boyd, Tetiana Parshakova, Ernest K. Ryu, Jaewook J. Suh

Keywords: Convex optimization, Distributed optimization, Decentralized optimization, ADMM, Alternating direction method of multipliers, PG-EXTRA, Performance estimation problem, Continuous-time analysis, first-order optimization, proximal methods

TL;DR: We design optimization algorithms using electric RLC circuits.

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.

Primary Area: Optimization (convex and non-convex, discrete, stochastic, robust)

Submission Number: 5661