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A fitness approximation assisted competitive swarm optimizer for large scale expensive optimization problems

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Abstract

Surrogate assisted meta-heuristic algorithms have received increasing attention over the past years due to the fact that many real-world optimization problems are computationally expensive. However, most existing surrogate assisted meta-heuristic algorithms are designed for small or medium scale problems. In this paper, a fitness approximation assisted competitive swarm optimizer is proposed for optimization of large scale expensive problems. Different from most surrogate assisted evolutionary algorithms that use a computational model for approximating the fitness, we estimate the fitness based on the positional relationship between individuals in the competitive swarm optimizer. Empirical study on seven widely used benchmark problems with 100 and 500 decision variables show that the proposed fitness approximation assisted competitive swarm optimizer is able to achieve competitive performance on a limited computational budget.

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Acknowledgments

This work was supported in part by National Natural Science Foundation of China (Nos. 61403272 and 61590922), an EPSRC grant (No. EP/M017869/1), the Joint Research Fund for Overseas Chinese, Hong Kong and Macao Scholars of the National Natural Science Foundation of China (No. 61428302), and State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, China.

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Authors and Affiliations

  1. Department of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan, 030024, Shanxi, People’s Republic of China

    Chaoli Sun

  2. Department of Computer Science, University of Surrey, Guildford, Surrey, GU2 7XH, UK

    Chaoli Sun & Yaochu Jin

  3. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, 110004, People’s Republic of China

    Chaoli Sun & Jinliang Ding

  4. School of Computer Science and Control Engineering, North University of China, Taiyuan, 030051, Shanxi, People’s Republic of China

    Jianchao Zeng

  5. Department of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan, 030024, Shanxi, People’s Republic of China

    Yaochu Jin

Authors
  1. Chaoli Sun
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  2. Jinliang Ding
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  3. Jianchao Zeng
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  4. Yaochu Jin
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Correspondence to Yaochu Jin.

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Sun, C., Ding, J., Zeng, J. et al. A fitness approximation assisted competitive swarm optimizer for large scale expensive optimization problems. Memetic Comp. 10, 123–134 (2018). https://doi.org/10.1007/s12293-016-0199-9

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  • DOI: https://doi.org/10.1007/s12293-016-0199-9

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