Fitness varying gravitational constant in GSA-Reference-Cited by-同舟云学术

Fitness varying gravitational constant in GSA

Published:2018-03-05 Issue:10 Volume:48 Page:3446-3461
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Bansal Jagdish Chand^ORCID,Joshi Susheel Kumar,Nagar Atulya K.

Funder

South Asian University

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

http://link.springer.com/article/10.1007/s10489-018-1148-8/fulltext.html

Reference19 articles.

1. Amoozegar M, Rashedi E (2014) Parameter tuning of gsa using doe. In: 2014 4th international conference on computer and knowledge engineering (ICCKE), pp 431–436

2. Bansal JC, Farswan P (2017) A novel disruption in biogeography-based optimization with application to optimal power flow problem. Appl Intell 46(3):590–615

3. Chen H, Li S, Tang Z (2011) Hybrid gravitational search algorithm with random-key encoding scheme combined with simulated annealing. IJCSNS 11(6):208

4. Doraghinejad M, Nezamabadi-pour H (2014) Black hole: a new operator for gravitational search algorithm. International Journal of Computational Intelligence Systems 7(5):809–826

5. Eiben AE, Schippers CA (1998) On evolutionary exploration and exploitation. Fundamenta Informaticae 35(1-4):35–50

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