An event-triggered collaborative neurodynamic approach to distributed global optimization

• DOI: 10.1016/j.neunet.2023.10.022
• Publication Date: 2023-10-19T04:01:58Z
• Authors: Zicong Xia; Yang Liu; Jun Wang
• Keywords: Global Optimization

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.