Abstract
A Novel Distributed Gravitational Search Algorithm With Multi-Layered Information Interaction
Highlights
Meta-heuristic algorithms (MHAs) have attracted more and more attention in the recent years [1]
In order to prevent the algorithm from falling into local optimization, we set up the historical information layer to manage the elite top layer by Eqs. (12) and (13)
Through the information interaction between the elite top layer and the historical information layer, MGSA realizes the better balance between exploitation and exploration
Summary
Meta-heuristic algorithms (MHAs) have attracted more and more attention in the recent years [1]. In [46], [47], [70], hierarchical, multi-layered and distributed structures are devised to optimize individuals’ interaction These mechanisms effectively alleviate the limitation of GSA such that its performance is improved. As one state-of-the-art GSA variant, DGSA [70] is the most recently proposed for function optimization and realworld optimization problems It uses a distributed framework and three-layered hierarchical structure to guide individuals’ search. The interaction among individuals needs to be further improved to accelerate the convergence of algorithm To realize such objective, this paper innovatively proposes a distributed gravitational search algorithm with multi-layer information interaction (MGSA) based on DGSA. The resultant MGSA optimizes the population structure and introduces historical information It effectively improves the information interaction among individuals.
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