Multiobjective Distributed Optimization via a Predefined-Time Multiagent Approach
Yang Liu, Zicong Xia, Weihua Gui
Abstract
In this study, we propose a predefined-time multiagent approach for multiobjective optimization. Predefined-time optimization is an optimization approach that can converge to a state that is extremely close to an optimal solution at a given time. A time-base generator is derived and applied to the optimization approaches for achieving predefined-time optimization. The multiobjective optimization problem is reformulated as a distributed optimization problem and, thus, solved in a private and safe manner. For distributed optimization, a multiagent system with time-base generators is developed for predefined-time optimization, and its convergence and speed are proven. Several examples confirm the validity of the results.