Chaotic bat algorithm

By Amir H. Gandomi, Xin-She Yang. Journal of Computer Science, 2014

497 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Biomedical Engineering

View Paper: https://www.semanticscholar.org/paper/0f9c08653e801764fc431f3d5f02c1f1286cc1ab

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In Artificial Intelligence

In Biomedical Engineering

Citations in the corpus

Nature-Inspired Optimization Algorithms: Challenges and Open Problems (2020, background): “…science, engineering and industry, from engineering optimization (Cagnina et al, 2008; Deb et al., 2002; Yang and Gandomi, 2012; Yang and Deb 2013; Gandomi and Yang, 2014; Chakri et al., 2017), and deep learning (Papa et al., 2017) to the coordination of swarming robots (Rango et al., 2018;…”
An improved discrete bat algorithm for symmetric and asymmetric Traveling Salesman Problems (2016, background): “In the same year, Gandomi and Yang proposed a CBA for robust global optimization ([Gandomi & Yang(2014)]).”
A survey on new generation metaheuristic algorithms (2019, methodology): “…(Formato, 2007), Curved Space Optimization (Moghaddam et al., 2012), Group Search Optimizer (He et al., 2006), Interior Search Algorithm (Gandomi, 2014), Soccer League Competition Algorithm (Moosavian and Roodsari, 2014), Seeker Optimization Algorithm (Dai et al., 2009), Random Forest…”
A novel chaotic salp swarm algorithm for global optimization and feature selection (2018, unknown): “Recently, chaos theory used to enhance these parameters [33].”
Bio inspired computing - A review of algorithms and scope of applications (2016, methodology): “Further chaotic AC CE PT ED M AN US CR IP T version of this algorithm (Gandomi and Yang, 2014) was developed to increase its global search mobility for robust global optimization.”
Metaheuristic algorithms for PID controller parameters tuning: review, approaches and open problems (2022, background): “In natural world, echolocation can last only a few thousandths of a second (up to around 8–10 ms) and also have a varying amplitude in the range of 25–150 kHz, which corresponds to air wavelengths of 2–14 mm (Gandomi and Yang, 2014).”
Chaotic Local Search-Based Differential Evolution Algorithms for Optimization (2021, methodology): “…properties have been used in other newly proposed swarm intelligence optimization algorithms, such as chaotic BBO [40], chaotic bat algorithm [29], [41], chaotic cuckoo search [42], chaotic fruit ﬂy optimization algorithm [43], chaotic krill herd algorithm [44], ﬁreﬂy algorithm with chaos [45],…”
Economic dispatch using chaotic bat algorithm (2016, methodology): “In [24], thirteen different chaotic sequences were tried to tune Ai to optimize three unimodal and three multimodal functions.”