A modified artificial bee colony algorithm

By Weifeng Gao, San-yang Liu. Computers & Operations Research, 2012

553 citations recorded by the source corpus.

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Bio inspired computing - A review of algorithms and scope of applications (2016, methodology): “The artificial bee colony algorithm (Karaboga, 2005; Gao & Liu, 2012) is a bio-inspired optimization algorithm which searches for an optimal numerical solution among a large number of alternatives.”
A self-adaptive artificial bee colony algorithm based on global best for global optimization (2017, methodology): “Different from the method proposed by Gao and Liu (2012), cosine function is replaced by sine function and the range of values become a half of original values in the novel algorithm.”
A new metaheuristic for numerical function optimization: Vortex Search algorithm (2015, methodology): “In the literature, in addition to the newly proposed optimization algorithms [17], [19], some extensions of the above-mentioned algorithms are also proposed [13], [32], [14], [15], [10], [42], [1], [43], [34], [23].”
A survey on new generation metaheuristic algorithms (2019, methodology): “Some of the well-known studies of HS are as follows: Lee and Geem (2005) describe an HS algorithm for engineering optimization problems having realnumber design variables. The proposed algorithm searches the space with a perfect state of harmony. It uses a random search instead of a gradient process”