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Neural Computing and Applications

, Volume 31, Supplement 2, pp 915–929 | Cite as

Multi-objective sine-cosine algorithm (MO-SCA) for multi-objective engineering design problems

  • Mohamed A. TawhidEmail author
  • Vimal Savsani
Original Article

Abstract

This paper proposes a novel and an effective multi-objective optimization algorithm named multi-objective sine-cosine algorithm (MO-SCA) which is based on the search technique of sine-cosine algorithm (SCA). MO-SCA employs the elitist non-dominated sorting and crowding distance approach for obtaining different non-domination levels and to preserve the diversity among the optimal set of solutions, respectively. The effectiveness of the method is measured by implementing it on multi-objective benchmark problems that have various characteristics of Pareto front such as convex, non-convex and discrete. This proposed algorithm is also checked for the multi-objective engineering design problems with distinctive features. Furthermore, we show the proposed algorithm effectively generates the Pareto front and is easy to implement and algorithmically simple.

Keywords

Multi-objective optimization Sine-cosine algorithm Multi-objective engineering design problems 

Notes

Acknowledgements

The research of the first author is supported in part by the Natural Sciences and Engineering Research Council of Canada (NSERC). The postdoctoral fellowship of the second author is supported by NSERC.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no competing interests.

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Copyright information

© The Natural Computing Applications Forum 2017

Authors and Affiliations

  1. 1.Department of Mathematics and Statistics, Faculty of ScienceThompson Rivers UniversityKamloopsCanada
  2. 2.Department of Mathematics and Computer Science, Faculty of ScienceAlexandria UniversityMoharam Bey, AlexandriaEgypt
  3. 3.Department of Mechanical EngineeringPandit Deendayal Petroleum UniversityGandhinagarIndia

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