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Open AccessArticle

Grouped Bees Algorithm: A Grouped Version of the Bees Algorithm

Electrical and Computer Engineering Department, University of Manitoba, Winnipeg, MB R3T 5V6, Canada
Electrical and Computer Engineering Faculty, Technical University of Kaiserslautern, 67663 Kaiserslautern, Germany
Electrical and Computer Engineering Faculty, K.N. Toosi University of Technology, Tehran, 163171419, Iran
Author to whom correspondence should be addressed.
Academic Editor: Kartik Gopalan
Computers 2017, 6(1), 5;
Received: 21 November 2016 / Revised: 12 January 2017 / Accepted: 24 January 2017 / Published: 28 January 2017
In many non-deterministic search algorithms, particularly those analogous to complex biological systems, there are a number of inherent difficulties, and the Bees Algorithm (BA) is no exception. The BA is a population-based metaheuristic search algorithm inspired by bees seeking nectar/pollen. Basic versions and variations of the BA have their own drawbacks. Some of these drawbacks are a large number of parameters to be set, lack of methodology for parameter setting and computational complexity. This paper describes a Grouped version of the Bees Algorithm (GBA) addressing these issues. Unlike its conventional version, in this algorithm bees are grouped to search different sites with different neighbourhood sizes rather than just discovering two types of sites, namely elite and selected. Following a description of the GBA, the results gained for 12 well-known benchmark functions are presented and compared with those of the basic BA, enhanced BA, standard BA and modified BA to demonstrate the efficacy of the proposed algorithm. Compared to the conventional implementations of the BA, the proposed version requires setting of fewer parameters, while producing the optimum solutions much more quickly. View Full-Text
Keywords: bees algorithm; Swarm Intelligence; evolutionary optimization; grouped bees algorithm bees algorithm; Swarm Intelligence; evolutionary optimization; grouped bees algorithm
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Nasrinpour, H.R.; Bavani, A.M.; Teshnehlab, M. Grouped Bees Algorithm: A Grouped Version of the Bees Algorithm. Computers 2017, 6, 5.

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