학술논문

Distributed Global Optimization by Annealing
Document Type
Conference
Source
2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2019 IEEE 8th International Workshop on. :181-185 Dec, 2019
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Signal Processing and Analysis
Convergence
Optimization
Annealing
Technological innovation
Distributed algorithms
Space exploration
Laplace equations
Distributed optimization
nonconvex optimization
multiagent systems
consensus + innovations
Language
Abstract
The paper considers distributed global minimization of a nonconvex function. We study a first-order consensus + innovations type algorithm that incorporates decaying additive Gaussian noise for annealing to converge to the set of global minima under certain technical assumptions. The paper presents simple methods for verifying that the required technical assumptions hold and illustrates it with a distributed target-localization application.