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International Conference on Swarm Intelligence

ICSI 2018: Advances in Swarm Intelligence pp 243–250Cite as

Applying a Multi-Objective Differential Evolution Algorithm in Translation Control of an Immersed Tunnel Element

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10941))

Abstract

Translation control of an immersed tunnel element under the water current flow is a typical optimization problem, which always emphasizes on short duration and high translation security. Various optimization approaches have been proposed to address this issue in previous works, but most of them take only one objective into consideration. Thus, it is solved as a single objective optimization problem. However, the translation control of the immersed tunnel element usually involves two or more conflicting objectives in actual situation. It’s necessary to convert the translation control problem into a multi-objective optimization problem to obtain effective solutions. Therefore, a recently proposed multi-objective differential evolution algorithm is employed to solve the problem in the present work. The translation model of the immersed tunnel element is introduced with three sub-objectives. Results indicate that a multi-objective differential evolution algorithm can provide a set of non-dominated solutions for assisting decision makers to complete the translation of the immersed tunnel element according to different targets and changing environment.

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Acknowledgment

We express our appreciation to the volume editor and reviewers for their constructive suggestions and comments on the earlier versions of the paper. This work was supported by the National Nature Science Foundation of china (No. 61603244). Here we would like to express our gratitude to them.

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Authors and Affiliations

  1. Logistics Research Center, Shanghai Maritime University, Shanghai, 201306, China

    Qing Liao & Qinqin Fan

Authors
  1. Qing Liao
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  2. Qinqin Fan
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Corresponding author

Correspondence to Qinqin Fan .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

  3. Tongji University, Shanghai, China

    Qirong Tang

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Liao, Q., Fan, Q. (2018). Applying a Multi-Objective Differential Evolution Algorithm in Translation Control of an Immersed Tunnel Element. In: Tan, Y., Shi, Y., Tang, Q. (eds) Advances in Swarm Intelligence. ICSI 2018. Lecture Notes in Computer Science(), vol 10941. Springer, Cham. https://doi.org/10.1007/978-3-319-93815-8_24

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  • DOI: https://doi.org/10.1007/978-3-319-93815-8_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-93814-1

  • Online ISBN: 978-3-319-93815-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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