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A Cooperative Evolution Framework Based on Fish Migration Optimization

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Advances in Intelligent Systems and Computing

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 268))

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Abstract

The Fish Migration Optimization (FMO) method was inspired by the fish swim and migration behaviors and has been proofed to be a brilliant algorithm for solving numerical optimization problems. However, FMO still has the problems of premature convergence, search stagnation and easy to fall into local optimum. In this paper, a cooperative evolution framework based on fish migration optimization (CEFMO) is proposed. By dividing the whole swarm into several subsets and introducing an evaluation function, at the end of each iteration, all the individuals are evaluated and when the evaluation result meets the conditions, the cooperative evolution is triggered. In order to verify the performance of the proposed algorithm, CEFMO was compared with serval iconic swarm intelligence algorithms, such as Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA) and Black Hole (BH) algorithm under CEC-2013 benchmark function and the result shows that the CEFMO is slightly better than the compared algorithms.

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Acknowledgment

This work is supported by the National Nature Science Foundation of China (No.61772102).

Author information

Authors and Affiliations

  1. Dalian Maritime University, Dalian, 116026, China

    Wenqi Li & Jeng-Shyang Pan

  2. Shandong University of Science and Technology, Qingdao, 266000, China

    Shu-Chuan Chu & Jeng-Shyang Pan

Authors
  1. Wenqi Li
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  2. Shu-Chuan Chu
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  3. Jeng-Shyang Pan
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Editor information

Editors and Affiliations

  1. Institute of Intelligent Media Technology, Communication, University of Zhejiang, Hangzhou City, China

    Jie-Fang Zhang

  2. College of Computer Science and Engineering, Shandong University of Science and Technology, Shandong, China

    Chien-Ming Chen

  3. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, Shandong, China

    Shu-Chuan Chu

  4. Department of Radio Communications and Video Technologies, Technical University of Sofia, Sofia, Bulgaria

    Roumen Kountchev

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Li, W., Chu, SC., Pan, JS. (2022). A Cooperative Evolution Framework Based on Fish Migration Optimization. In: Zhang, JF., Chen, CM., Chu, SC., Kountchev, R. (eds) Advances in Intelligent Systems and Computing. Smart Innovation, Systems and Technologies, vol 268. Springer, Singapore. https://doi.org/10.1007/978-981-16-8048-9_9

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