Bat algorithm: literature review and applications

By Xin-She Yang, Xingshi He. International Journal of Bio-Inspired Computation (IJBIC), 2013

972 citations recorded by the source corpus.

Bat algorithm BA is a bio-inspired algorithm developed by Xin-She Yang in 2010 and BA has been found to be very efficient. As a result, the literature has expanded significantly in the last three years. This paper provides a timely review of the bat algorithm and its new variants. A wide range of diverse applications and case studies are also reviewed and summarised briefly here. In addition, we also discuss the essence of an algorithm and the links between algorithms and self-organisation. Further research topics are also discussed.

Subfields: Artificial Intelligence, Biomedical Engineering

View Paper: https://www.semanticscholar.org/paper/4ee55ca511542d8c58c63b0512b50f49d53845e7

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Citations in the corpus

Bio inspired computing - A review of algorithms and scope of applications (2016, background): “This algorithm can provide a good balance of exploitation and exploration (Yang & He, 2013), since it requires far fewer function evaluations, thereby reducing computational complexity.”
Bio-inspired computation: Where we stand and what's next (2019, methodology): “ever the threat may be, bio-inspired methods have been lately applied to improve the overall response and resiliency of computerbased systems, thereby facing with success common computer attacks such as phishing [379], eavesdropping [380], Denial-ofService or spoofing [381].”
A Comprehensive Review of Swarm Optimization Algorithms (2015, background): “This frequency equation has direct influence on the velocity equation which determines the direction in search space [118 – 120].”
Building an efficient intrusion detection system based on feature selection and ensemble classifier (2019, neutral): “solution vector to a problem of interest. Among the n bats in the population, the current best solution x∗found so far can be archived during the iterative search process. Defined by Yang on the paper[20], the updating rules for the location xt i and velocityv t i at time step t are given by fi = fm”
A comprehensive survey on recent metaheuristics for feature selection (2022, methodology): “Echolocation can be formalized as a technique to optimize an objective function [129].”
An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges (2023, background): “(2020) 60 Bar Systems (BS) Del Acebo and de-la Rosa (2008) 61 Bat Algorithm (BA) Yang and He (2013) 62 Bat Inspired Algorithm (BIA) Yang (2010b) 63 Bat Intelligence (BI) Malakooti et al.”
An improved discrete bat algorithm for symmetric and asymmetric Traveling Salesman Problems (2016, methodology): “For this reason, if any reader wants more information regarding the possible applications of BA, we recommend the reading of the literature review paper presented in ([Yang & He(2013)]).”
Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images (2019, background): “These rules are formed by the reduction of errors by bats [19]: Segmentation accuracy is sensed by echolocation by bats.”