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Micro Multi-objective Genetic Algorithm

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Numerical Simulation-based Design

Abstract

As a global search approach based on population evolution, the genetic algorithm (GA) has great advantage in solving MOPs. For most of the multi-objective genetic algorithms (MOGAs), a large size of evolutionary population is adopted in the process of fitness evaluation and selection operation to make the evolution direction towards the non-dominated optimal solution set and to guarantee the population diversity and the distribution uniformity.

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Authors and Affiliations

  1. Hunan University, Changsha, Hunan, China

    Xu Han

  2. College of Mechanical and Vehicle Engineering, Hunan University, Changsha, Hunan, China

    Jie Liu

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  1. Xu Han
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  2. Jie Liu
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Correspondence to Xu Han .

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Han, X., Liu, J. (2020). Micro Multi-objective Genetic Algorithm. In: Numerical Simulation-based Design. Springer, Singapore. https://doi.org/10.1007/978-981-10-3090-1_9

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  • DOI: https://doi.org/10.1007/978-981-10-3090-1_9

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3089-5

  • Online ISBN: 978-981-10-3090-1

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