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An Elitist Non-dominated Sorting Hybrid Evolutionary Algorithm for Multi-objective Constrained Ship Arrangements Optimization Problem

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Bio-inspired Computing: Theories and Applications (BIC-TA 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 791))

Abstract

As the complexity of ship arrangements increases, general arrangements optimization technology based on evolutionary algorithms has emerged, giving enormous potential to assist designers in enhancing the range of alternative arrangements and in expediting the design process. This paper presents a hybrid evolutionary algorithm to handle the multi-objective constrained arrangements optimization problem based on elitist non-dominated sorting strategy. To enhance the efficiency of optimization, a hybrid evolutionary algorithm that couples an NSGA-II with a stochastic local search technique is used to find feasible solutions rapidly and facilitate local optimization. However, the algorithm that can rapidly find feasible solutions is also expected to contribute to better optimization. It has also been observed that lack of diversity of potential solutions leads to a local optimal solution which means the coherent arrangements could not be discovered. Hence, a modified replacement strategy is proposed to overcome this drawback. The final experimental results illustrate that the algorithm is capable of generating coherent arrangements.

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Authors and Affiliations

  1. Wuhan University of Technology, Wuhan, China

    Hao Wang, Shunhuai Chen & Liang Luo

Authors
  1. Hao Wang
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  2. Shunhuai Chen
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  3. Liang Luo
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Corresponding author

Correspondence to Hao Wang .

Editor information

Editors and Affiliations

  1. School of Automation, Huazhong University of Science and Technology, Wuhan, China

    Cheng He

  2. Automation College, Harbin Engineering University, Harbin, China

    Hongwei Mo

  3. School of Automation, Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  4. Automation College, Harbin Engineering University, Harbin, China

    Yuxin Zhao

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Wang, H., Chen, S., Luo, L. (2017). An Elitist Non-dominated Sorting Hybrid Evolutionary Algorithm for Multi-objective Constrained Ship Arrangements Optimization Problem. In: He, C., Mo, H., Pan, L., Zhao, Y. (eds) Bio-inspired Computing: Theories and Applications. BIC-TA 2017. Communications in Computer and Information Science, vol 791. Springer, Singapore. https://doi.org/10.1007/978-981-10-7179-9_5

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  • DOI: https://doi.org/10.1007/978-981-10-7179-9_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7178-2

  • Online ISBN: 978-981-10-7179-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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