Multiobjective Adaptive Wind Driven Optimization

Zikri Bayraktar, Muge Komurcu

2016

Abstract

In this work, we introduce a new nature-inspired multiobjective numerical optimization algorithm where Pareto dominance is incorporated into Adaptive Wind Driven Optimization for handling multiobjective optimization problems and named as Multiobjective Adaptive Wind Driven Optimization (MO-AWDO) method. This new approach utilizes an external repository of air parcels to record the non-dominated Pareto-fronts found at each iteration via the fast non-dominated sorting algorithm, which are then utilized in the velocity update equation of the AWDO for the next iteration. The performance of the MO-AWDO is tested on five different numerical test functions with two objectives and results indicate that the MO-AWDO offers a very competitive approach compared to well-known methods in the published literature even performing better than NSGA-II for ZDT4 test function.

References

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Paper Citation


in Harvard Style

Bayraktar Z. and Komurcu M. (2016). Multiobjective Adaptive Wind Driven Optimization . In Proceedings of the 8th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2016) ISBN 978-989-758-201-1, pages 115-120. DOI: 10.5220/0006031801150120


in Bibtex Style

@conference{ecta16,
author={Zikri Bayraktar and Muge Komurcu},
title={Multiobjective Adaptive Wind Driven Optimization},
booktitle={Proceedings of the 8th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2016)},
year={2016},
pages={115-120},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006031801150120},
isbn={978-989-758-201-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2016)
TI - Multiobjective Adaptive Wind Driven Optimization
SN - 978-989-758-201-1
AU - Bayraktar Z.
AU - Komurcu M.
PY - 2016
SP - 115
EP - 120
DO - 10.5220/0006031801150120