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Bat-inspired algorithm is a [[metaheuristic]] [[optimization]] algorithm developed by Xin-She Yang in 2010.<ref>X. S. Yang, A New Metaheuristic Bat-Inspired Algorithm, in: Nature Inspired Cooperative Strategies for Optimization (NISCO 2010) (Eds. J. R. Gonzalez et al.), Studies
in Computational Intelligence, Springer Berlin, 284, Springer, 65-74 (2010). http://arxiv.org/abs/1004.4170
== Algorithm Description ==
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== Multi-objective Bat Algorithm (MOBA) ==
Using a simple weighted sum with random weights, a very effective but yet simple multiobjective bat algorithm (MOBA) has been developed to solve multiobjective engineering design tasks.<ref>X. S. Yang, bat algorithm for multi-objective optimisation, Int. J. Bio-Inspired Computation, Vol. 3, 267-274 (2011).
NSGA-II produces very competitive results with good efficiency.<ref>
approach for the brushless DC wheel motor problem, IEEE Trans. Magnetics, Vol. 48 (2), 947-950 (2012).</ref>
== Applications ==
Bat algorithm has been used for engineering design,<ref>X. S. Yang and A. H. Gandomi, Bat algorithm: a novel approach for global engineering optimization, Engineering Computations, Vol. 29, No. 5, pp. 464-483 (2012).</ref>
A fuzzy bat clustering method has been developed to solve ergonomic workplace problems<ref>Khan, K., Nikov, A., Sahai A., A Fuzzy Bat Clustering Method for Ergonomic Screening of Office Workplaces,S3T 2011,
Advances in Intelligent and Soft Computing, 2011, Volume 101/2011, 59-66 (2011).</ref>
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[[Category:Heuristic algorithms]]
[[Category:
[[Category:Optimization algorithms and methods]]
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