A multi-objective Artificial Bee Colony for optimizing multi-objective problems

This work proposes a multi-objective artificial bee colony (MOABC) for optimizing problems with multiple objectives. We have adapted the original Artificial Bee Colony (ABC) algorithm to multi objective problems with a grid-based approach for maintaining and adaptively assessing the Pareto front. Th...

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Veröffentlicht in:2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE) Jg. 5; S. V5-277 - V5-281
Hauptverfasser: Hedayatzadeh, Ramin, Hasanizadeh, Bahareh, Akbari, Reza, Ziarati, Koorush
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.08.2010
Schlagworte:
artificial bee colony
Benchmark testing
Lead
multi-objective optimization
ISBN:1424465397, 9781424465392
ISSN:2154-7491
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Beschreibung
Zusammenfassung:This work proposes a multi-objective artificial bee colony (MOABC) for optimizing problems with multiple objectives. We have adapted the original Artificial Bee Colony (ABC) algorithm to multi objective problems with a grid-based approach for maintaining and adaptively assessing the Pareto front. The Pareto set is used to control the flying behaviours of the individuals and structuring the bee colony. The proposed algorithm was evaluated upon numerical benchmark problems. Our experimental results indicate that the proposed approach is highly competitive compared to other algorithms considered in this work.
ISBN:1424465397
9781424465392
ISSN:2154-7491
DOI:10.1109/ICACTE.2010.5579761