An event-triggered collaborative neurodynamic approach to distributed global optimization

• Published in: Neural networks Vol. 169; pp. 181 - 190
• Main Authors: Xia, Zicong, Liu, Yang, Wang, Jun
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.01.2024
• Subjects: Collaborative neurodynamic optimization; Distributed optimization; Event-triggered communication; Global optimization; Heuristics; HVAC systems; Neural Networks, Computer; Recurrent neural networks; Collaborative neurodynamic optimization; Distributed optimization; Global optimization; Recurrent neural networks; HVAC systems; Event-triggered communication
• ISSN: 0893-6080; 1879-2782; 1879-2782
• DOI: 10.1016/j.neunet.2023.10.022

In this paper, we propose an event-triggered collaborative neurodynamic approach to distributed global optimization in the presence of nonconvexity. We design a projection neural network group consisting of multiple projection neural networks coupled via a communication network. We prove the convergence of the projection neural network group to Karush–Kuhn–Tucker points of a given global optimization problem. To reduce communication bandwidth consumption, we adopt an event-triggered mechanism to liaise with other neural networks in the group with the Zeno behavior being precluded. We employ multiple projection neural network groups for scattered searches and re-initialize their states using a meta-heuristic rule in the collaborative neurodynamic optimization framework. In addition, we apply the collaborative neurodynamic approach for distributed optimal chiller loading in a heating, ventilation, and air conditioning system.