Most of the multiobjective evolutionary algorithm inherently has heavy computational burden, so it takes a long processing time. For this reason, many researches for reducing computational time have been carried out, in particular by using distributed computing such as multi-thread coding, GPU coding, etc. In this paper, multi-thread coding is used to reduce computational time and applied to multiobjective quantum-inspired evolutionary algorithm (MQEA). In MQEA, nondominated sorting and crowding distance assignment which take a long time are carried out in each subpopulation. By multi-thread coding, the processes in each subpopulation can be performed simultaneously. To demonstrate the effectiveness of the proposed distributed MQEA (DMQEA), comparisons with single-thread and multi-thread are carried out for seven DTLZ functions. © 2013 Springer-Verlag.
CITATION STYLE
Ryu, S. J., & Kim, J. H. (2013). Distributed multiobjective quantum-inspired evolutionary algorithm (DMQEA). In Advances in Intelligent Systems and Computing (Vol. 208 AISC, pp. 663–670). Springer Verlag. https://doi.org/10.1007/978-3-642-37374-9_63
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