Multiagent based state transition algorithm for global optimization
Published in arXiv (Cornell University) • Mar 5, 2021
NobleIDNI0P92W82R68S70
Authors:
Xiaojun Zhou
Abstract
In this paper, a novel multiagent based state transition optimization algorithm with linear convergence rate named MASTA is constructed. It first generates an initial population randomly and uniformly. Then, it applies the basic state transition algorithm (STA) to the population and generates a new ...
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