Volume 9, Issue 4, August 2016, Pages 652 - 665
Modified Black Hole Algorithm with Genetic Operators
Authors
Saber Yaghoobisaber.yaghoobi@gmail.com, Hamed Mojallalimojallali@guilan.ac.ir
Electrical Engineering Department, Faculty of Engineering,University of Guilan, Rasht, PO Box 3756, Guilan Province, Iran
Received 3 November 2015, Accepted 12 March 2016, Available Online 1 August 2016.
- DOI
- 10.1080/18756891.2016.1204114How to use a DOI?
- Keywords
- Black Hole; Nature-inspired optimization; Metaheuristic algorithm; Benchmarking
- Abstract
In this paper, a modified version of nature-inspired optimization algorithm called Black Hole has been proposed. The proposed algorithm is population based and consists of genetic algorithm operators in order to improve optimization results. The proposed method enhances Black Hole algorithm performance by searching space with more diversity. The modified Black Hole algorithm has been applied to a well-known benchmark. The experimental results show that the modified Black Hole algorithm outperforms compared to some prominent optimization algorithms.
- Copyright
- © 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
- Open Access
- This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).
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TY - JOUR AU - Saber Yaghoobi AU - Hamed Mojallali PY - 2016 DA - 2016/08/01 TI - Modified Black Hole Algorithm with Genetic Operators JO - International Journal of Computational Intelligence Systems SP - 652 EP - 665 VL - 9 IS - 4 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2016.1204114 DO - 10.1080/18756891.2016.1204114 ID - Yaghoobi2016 ER -