Distributed and Anytime Algorithm for Network Optimization Problems with Separable Structure

TL;DR

This paper introduces a distributed, anytime algorithm for solving constrained optimization problems with separable structure, ensuring convergence and feasibility invariance, supported by theoretical analysis and simulations.

Contribution

The paper presents a novel distributed dynamical system algorithm that guarantees convergence and feasibility invariance for separable constrained optimization problems.

Findings

Algorithm converges to the optimal solution.

Feasible set remains invariant during the process.

Simulations confirm theoretical results.

Abstract

This paper considers the problem of designing a dynamical system to solve constrained optimization problems in a distributed way and in an anytime fashion (i.e., such that the feasible set is forward invariant). For problems with separable objective function and constraints, we design an algorithm with the desired properties and establish its convergence. Simulations illustrate our results.