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Multi-objective Optimization Algorithm Based on Uniform Design and Differential Evolution

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Artificial Intelligence Algorithms and Applications (ISICA 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1205))

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Abstract

The multi-objective optimization problem is an important research direction in the field of optimization. Because the traditional mathematical programming method often cannot achieve the optimal global solution, the researchers introduced the heuristic method into the multi-objective optimization problem. The heuristic method is a method of searching based on empirical rules, which can get the optimal solution or solution set of problems in the limited search space. In this paper, we proposed a multi-objective evolutionary algorithm based on uniform design and differential evolution, which use the uniform design table to construct the weight vector and utilize the crossover in differential evolution and mutation process to replace the simulated binary intersection and the simulated polynomial variation. Compared with the classical algorithm, the experimental results show that the improved algorithm is superior to the original algorithm.

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Acknowledgement

This work was partially supported by National Natural Science Foundation of China (61902339, 61876136), the China Postdoctoral Science Foundation (2018M633585), Natural Science Basic Research Plan in Shaanxi Province of China (No. 2018JQ6060), and Google Supported Industry-University Cooperation and Education Project, Doctoral Starting up Foundation of Yan’an University (YDBK2019-06).

Author information

Authors and Affiliations

  1. College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, 712100, China

    Jinrong He, Dongjian He & Aiqing Shi

  2. College of Mathematics and Computer Science, Yan’an University, Yan’an, 716000, China

    Jinrong He

  3. Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China

    Jinrong He, Dongjian He & Aiqing Shi

  4. School of Computer, Wuhan University, Wuhan, 430070, China

    Guoliang He

Authors
  1. Jinrong He
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  2. Dongjian He
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  3. Aiqing Shi
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  4. Guoliang He
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Corresponding author

Correspondence to Dongjian He .

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Editors and Affiliations

  1. South China Agricultural University, Guangzhou, China

    Kangshun Li

  2. Jiangxi University of Science and Technology, Ganzhou, China

    Wei Li

  3. South China Agricultural University, Guangzhou, China

    Hui Wang

  4. The University of Aizu, Aizu-Wakamatsu, Fukushima, Japan

    Yong Liu

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He, J., He, D., Shi, A., He, G. (2020). Multi-objective Optimization Algorithm Based on Uniform Design and Differential Evolution. In: Li, K., Li, W., Wang, H., Liu, Y. (eds) Artificial Intelligence Algorithms and Applications. ISICA 2019. Communications in Computer and Information Science, vol 1205. Springer, Singapore. https://doi.org/10.1007/978-981-15-5577-0_14

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  • DOI: https://doi.org/10.1007/978-981-15-5577-0_14

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-5576-3

  • Online ISBN: 978-981-15-5577-0

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