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Published in: Soft Computing 23/2019

06-02-2019 | Methodologies and Application

Artificial Bee Colony algorithm with improved search mechanism

Authors: Amreek Singh, Kusum Deep

Published in: Soft Computing | Issue 23/2019

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Abstract

In a preceding study, authors critically analysed the functional behaviour of Artificial Bee Colony (ABC) algorithm in view of some of its reported search limitations and offered directions for performance improvements. Accordingly, an improved ABC (IABC) algorithm is proposed with inclusion of three features: (1) dynamic update of probability values of food sources after every successful new search under the onlooker bees operator, (2) Allocation of variable ‘effective limit’ to each food source based upon its food quality instead of global fixed ‘limit’ and (3) insulation of best-so-far solution from scout bee operator. The additional features render substantial improvements in search abilities of ABC algorithm. The experiments with classical and CEC’2014 benchmark test functions confirm the supremacy of IABC algorithm over basic ABC algorithm as well as some of its variants and other evolutionary algorithms. Notably, the IABC algorithm does not introduce any new control parameter or hybridization with any other operator and maintains almost same level of computational complexity.

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Metadata
Title
Artificial Bee Colony algorithm with improved search mechanism
Authors
Amreek Singh
Kusum Deep
Publication date
06-02-2019
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 23/2019
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-019-03785-y

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