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Chaos-driven Discrete Artificial Bee Colony

Authors: Magdalena Metlicka; Donald Davendra;

Chaos-driven Discrete Artificial Bee Colony

Abstract

In this paper, a chaos driven Discrete Artificial Bee Algorithm is introduced. The main premise of this work is to ascertain if using chaos maps in lieu of standard pseudorandom number generators can improve the performance of the canonical algorithm. Nine unique chaos maps are embedded in the Discrete Artificial Bee Algorithm alongside the Mersenne twister and evaluated on the lot-streaming flowshop scheduling problem with setup time. Based on the obtained results, a number of chaotic maps significantly improve the performance of the algorithm. Additionally, the new algorithm is favourably compared with the chaos driven Enhanced Differential Evolution algorithm for the same problem.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Average
Top 10%
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