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Semi-Markov Model of a Swarm Functioning Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Teaching-Learning-Based Artificial Bee Colony

Authors : Xu Chen, Bin Xu

Published in: Advances in Swarm Intelligence

Publisher: Springer International Publishing

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Abstract

This paper proposes a new hybrid metaheuristic algorithm called teaching-learning artificial bee colony (TLABC) for function optimization. TLABC combines the exploitation of teaching learning based optimization (TLBO) with the exploration of artificial bee colony (ABC) effectively, by employing three hybrid search phases, namely teaching-based employed bee phase, learning-based onlooker bee phase, and generalized oppositional scout bee phase. The performance of TLABC is evaluated on 30 complex benchmark functions from CEC2014, and experimental results show that TLABC exhibits better results compared with previous TLBO and ABC algorithms.

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previous chapter New Binary Artificial Bee Colony for the 0-1 Knapsack Problem
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Metadata
Title
Teaching-Learning-Based Artificial Bee Colony
Authors
Xu Chen
Bin Xu
Copyright Year
2018
Book
Advances in Swarm Intelligence

Print ISBN: 978-3-319-93814-1

Electronic ISBN: 978-3-319-93815-8

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-93815-8_17

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