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A Novel Mutation and Crossover Operator for Multi-objective Differential Evolution

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Computational Intelligence and Intelligent Systems (ISICA 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 873))

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Abstract

Differential evolution is a simple evolutionary algorithm by simulating Darwinian evolution principle where the population of individuals are evolved and adapted with some reproduction mechanisms such as mutation, crossover and selection operator in the computer environment. During a mutation in the nature, only a few vectors of the individuals will be mutated instead of a mutation in whole vectors. Also during a crossover operation, there is still a mutation chance for individuals. This work proposed a novel mutation and crossover operation for multi-objective differential evolution inspired by above, named as NMCO-MODE. In the NMCO-MODE, offspring is allowed to mutate during a crossover as it is same for living individuals in nature, or keep some of its vector same after a mutation. At last, the NMCO-MODE is tested with multi-objective optimization problems (MOP), it’s found out that the new mechanism significantly improved performance of differential evolution algorithm. It has sharp convergence character and gets stuck in local minima less frequently than other multi-objective evolutionary algorithms.

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Acknowledgement

This work was supported by the National Nature Science Foundation of China (No. 61370185, 61402217), Guangdong Higher School Scientific Innovation Project (No. 2014KTSCX188), the outstanding young teacher training program of the Education Department of Guangdong Province (YQ2015158); and Guangdong Provincial Science and Technology Plan Projects (No. 2016A010101034, 2016A010101035). Guangdong Provincial High School of International and Hong Kong, Macao and Taiwan cooperation and innovation platform and major international cooperation projects (No. 2015KGJHZ027).

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Authors and Affiliations

  1. Department of Computer, City College of Dongguan University of Technology, Dongguan, 523419, China

    Qingxia Li

  2. School of Computer, Dongguan University of Technology, Dongguan, 523808, China

    Wenhong Wei

Authors
  1. Qingxia Li
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  2. Wenhong Wei
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Corresponding author

Correspondence to Wenhong Wei .

Editor information

Editors and Affiliations

  1. College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China

    Kangshun Li

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

    Wei Li

  3. Chemical and Petroleum Engineering, University of Calgary, Calgary, Alberta, Canada

    Zhangxing Chen

  4. School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu, Fukushima, Japan

    Yong Liu

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Li, Q., Wei, W. (2018). A Novel Mutation and Crossover Operator for Multi-objective Differential Evolution. In: Li, K., Li, W., Chen, Z., Liu, Y. (eds) Computational Intelligence and Intelligent Systems. ISICA 2017. Communications in Computer and Information Science, vol 873. Springer, Singapore. https://doi.org/10.1007/978-981-13-1648-7_12

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  • DOI: https://doi.org/10.1007/978-981-13-1648-7_12

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1647-0

  • Online ISBN: 978-981-13-1648-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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