Department of Computer Engineering, Esfarayen University of Technology, Esfarayen, North Khorasan, Iran
Abstract
Most real-world problems exhibit a multimodal property, meaning that there are several global or local optimal solutions present in the landscape of the function. Recent research has paid significant attention to multimodal optimization. This paper presents a novel niching Genetic Algorithm (GA) that is designed for multimodal optimization. Our approach involves the formation of niches based on individual positions, and the genetic operators are formulated to avoid disrupting these niches. Experimental analysis confirms that the proposed method outperforms previously introduced methods.
Bazoobandi, H. (2022). A Niching Ring Topology Genetic Algorithm for Multimodal Optimization. Transactions on Machine Intelligence, 5(2), 115-121.
MLA
H.A. Bazoobandi. "A Niching Ring Topology Genetic Algorithm for Multimodal Optimization". Transactions on Machine Intelligence, 5, 2, 2022, 115-121.
HARVARD
Bazoobandi, H. (2022). 'A Niching Ring Topology Genetic Algorithm for Multimodal Optimization', Transactions on Machine Intelligence, 5(2), pp. 115-121.
VANCOUVER
Bazoobandi, H. A Niching Ring Topology Genetic Algorithm for Multimodal Optimization. Transactions on Machine Intelligence, 2022; 5(2): 115-121.
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