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A novel multi-objective optimization algorithm based on artificial algae for multi-objective engineering design problems

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Abstract

There are many diverse fields and applications such as data mining, engineering, operations research, economics, and science can be formulated as multi-objective optimization problems. In this paper, we describe and propose a novel and a useful multi-objective artificial algae algorithm (MO-AAA) to solve multi-objective engineering design problems. Our proposed algorithm, (MO-AAA), is based on the search technique of artificial algae algorithm(AAA) algorithm. MO-ADA applies the elitist non-dominated sorting and crowding distance approach to preserve the diversity among the optimal set of solutions and obtains various non-domination levels, respectively. Also, we evaluate the effectiveness of the proposed algorithm by applying it on different multi-objective benchmark problems (20 challenging benchmark problems from CEC 2009 for unconstrained and constrained multi-objective optimization problems) and engineering design benchmark problems with distinctive features. Finally, our results show that MO-AAA efficiently generates the Pareto front and is easy to implement, promising and competitive compared to other state-of-the-art algorithms considered in this work.

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Acknowledgments

We are thankful to the editor-in-chief and referees for their insightful and constructive comments and suggestions that significantly improved the clarity of the paper. The research of the 1st author is supported in part by the Natural Sciences and Engineering Research Council of Canada (NSERC). The postdoctoral fellowship of the 2nd author is supported by NSERC.

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Authors and Affiliations

  1. Department of Mathematics and Statistics, Faculty of Science, Thompson Rivers University, Kamloops, BC, V2C 0C8, Canada

    Mohamed A. Tawhid

  2. Department of Mathematics and Computer Science, Faculty of Science, Alexandria University, Moharam Bey, 21511, Alexandria, Egypt

    Mohamed A. Tawhid

  3. Department of Mechanical Engineering, Pandit Deendayal Petroleum University, Gandinagar, Gujarat, India

    Vimal Savsani

  4. Postdoctoral Fellow, Department of Mathematics and Statistics, Faculty of Science, Thompson Rivers University, Kamloops, BC, V2C 0C8, Canada

    Vimal Savsani

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Tawhid, M.A., Savsani, V. A novel multi-objective optimization algorithm based on artificial algae for multi-objective engineering design problems. Appl Intell 48, 3762–3781 (2018). https://doi.org/10.1007/s10489-018-1170-x

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