Gbest-guided artificial bee colony algorithm for numerical function optimization

By Guopu Zhu, Sam Kwong. Applied Mathematics and Computation, 2010

1,263 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/c1380d8e3234451ec53e121d1ce8bbe7b739b29f

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In Artificial Intelligence

In Computational Theory and Mathematics

Citations in the corpus

A Novel Artificial Bee Colony Algorithm Based on Modified Search Equation and Orthogonal Learning (2013, methodology): “In this section, ABC-based algorithms are applied to minimize a set of 20 scalable benchmark functions of dimensions D = 15, 30, or 60 [9], [17], [36], [38] and a set of 2 func-”
A conceptual comparison of the Cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms (2011, methodology): “9, the standard system-equation of a modified ABC algorithm (Zhua and Kwongb 2010) is obtained as, vr1,h ← Xr1,h + φr1,h(Xr1,h − Xr2,h)+ ψr1,h(Gbesth − Xr1,h) (10) where Gbest is the best pattern found by the pattern matrix.”
Spider Monkey Optimization algorithm for numerical optimization (2014, methodology): “The solution search equation of ABC is significantly influenced by a random quantity which helps in exploration at the cost of exploitation of the search space [42].”
Rosenbrock artificial bee colony algorithm for accurate global optimization of numerical functions (2011, methodology): “ABC methods that use chaotic maps as efficient alternatives to pseudorandom sequences were proposed by Alatas [3], and global-bestsolution-guided ABC was proposed by Zhu and Kwong [75].”
Improved artificial bee colony algorithm for global optimization (2011, methodology): “At last, IABC is compared with CABC [18], GABC [14] and RABC [17].”
A self-adaptive artificial bee colony algorithm based on global best for global optimization (2017, methodology): “The performance of SABC-GB was compared with that of GABC (Zhu and Kwong 2010), ABC/best/1 (Gao et al. 2012), and ABC/best/2 (Gao et al. 2012).”
Evolutionary population dynamics and grey wolf optimizer (2014, methodology): “• ABC was equipped with the global best concept of PSO in [28].”
Overview of energy storage systems in distribution networks: Placement, sizing, operation, and power quality (2018, background): “For instance, the ABC has poor local search ability but strong global search capability [260], while the reverse is true for PSO [261].”