GNSD: a Gradient-Tracking Based Nonconvex Stochastic Algorithm for Decentralized Optimization

2019 ◽  
Author(s):  
Songtao Lu ◽  
Xinwei Zhang ◽  
Haoran Sun ◽  
Mingyi Hong
Keyword(s):  
Stochastic Algorithm ◽  
Decentralized Optimization

scholarly journals Decentralized Optimization Over Tree Graphs

2021 ◽  
Author(s):  
Yuning Jiang ◽  
Dimitris Kouzoupis ◽  
Haoyu Yin ◽  
Moritz Diehl ◽  
Boris Houska
Keyword(s):  
Decentralized Optimization ◽  
Tree Graphs

scholarly journals Demand response through decentralized optimization in residential areas with wind and photovoltaics

Energy ◽  
2021 ◽  
Vol 223 ◽  
pp. 119984
Author(s):  
Thomas Dengiz ◽  
Patrick Jochem ◽  
Wolf Fichtner
Keyword(s):  
Demand Response ◽  
Residential Areas ◽  
Decentralized Optimization

scholarly journals Improving Computational Efficiency in Crowded Task Allocation Games with Coupled Constraints

2019 ◽  
Vol 9 (10) ◽  
pp. 2117
Author(s):  
Ming Chong Lim ◽  
Han-Lim Choi
Keyword(s):  
Task Allocation ◽  
Random Sampling ◽  
Scheduling Algorithm ◽  
Stochastic Algorithm ◽  
Speed Of Convergence ◽  
Temporal Dependence ◽  
Real World Applications ◽  
Coupled Constraints ◽  
Multi Agent ◽  
Feasible Solutions

Multi-agent task allocation is a well-studied field with many proven algorithms. In real-world applications, many tasks have complicated coupled relationships that affect the feasibility of some algorithms. In this paper, we leverage on the properties of potential games and introduce a scheduling algorithm to provide feasible solutions in allocation scenarios with complicated spatial and temporal dependence. Additionally, we propose the use of random sampling in a Distributed Stochastic Algorithm to enhance speed of convergence. We demonstrate the feasibility of such an approach in a simulated disaster relief operation and show that feasibly good results can be obtained when the confirmation and sample size requirements are properly selected.

scholarly journals Decentralized Optimization for a Novel Control Structure of HVAC System

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Shiqiang Wang ◽  
Jianchun Xing ◽  
Ziyan Jiang ◽  
Juelong Li
Keyword(s):  
Control System ◽  
Decentralized Control ◽  
Control Structure ◽  
Optimization Method ◽  
Labor Cost ◽  
Smart Device ◽  
Hvac System ◽  
Decentralized Optimization ◽  
System A ◽  
Novel Method

A decentralized control structure is introduced into the heating, ventilation, and air conditioning (HVAC) system to solve the high maintenance and labor cost problem in actual engineering. Based on this new control system, a decentralized optimization method is presented for sensor fault repair and optimal group control of HVAC equipment. Convergence property of the novel method is theoretically analyzed considering both convex and nonconvex systems with constraints. In this decentralized control system, traditional device is fitted with a control chip such that it becomes a smart device. The smart device can communicate and operate collaboratively with the other devices to accomplish some designated tasks. The effectiveness of the presented method is verified by simulations and hardware tests.

scholarly journals A General Framework for Decentralized Optimization With First-Order Methods

2020 ◽  
Vol 108 (11) ◽  
pp. 1869-1889
Author(s):  
Ran Xin ◽  
Shi Pu ◽  
Angelia Nedic ◽  
Usman A. Khan
Keyword(s):  
General Framework ◽  
Decentralized Optimization ◽  
First Order ◽  
First Order Methods

MODELLING AEROSOL DYNAMICS : A STOCHASTIC ALGORITHM

2001 ◽  
Vol 32 ◽  
pp. 1037-1038
Author(s):  
E. DEBRY ◽  
B. JOURDAIN ◽  
B. SPORTISSE
Keyword(s):  
Stochastic Algorithm ◽  
Aerosol Dynamics
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