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A Novel Self-adaptive Differential Evolution Algorithm with Population Size Adjustment Scheme

  • Research Article - Computer Engineering and Computer Science
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Abstract

It is well known that mutation scale factor, the crossover constant, and the population size are three main control parameters of the differential evolution (DE) algorithm. These parameters are of great importance to the efficiency of a DE algorithm. However, finding appropriate settings is a difficult task. In this work, a self-adaptive DE with population adjustment scheme (SAPA) is proposed to tune the size of offspring population. The novel algorithm involves two DE strategies and two population adjustment schemes. The performance of the SAPA algorithm is evaluated on a set of benchmark problems. Simulation results show that the proposed algorithm is better than, or at least comparable with, other classic or adaptive DE algorithms. Performance comparisons with some other well-known evolutionary algorithms from literatures are also presented.

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Authors and Affiliations

  1. College of Information Science and Technology, Donghua University, Shanghai, 201620, People’s Republic of China

    Shuguang Zhao & Xu Wang

  2. College of Automotive Engineering, Shanghai University of Engineering and Science, Shanghai, 201620, People’s Republic of China

    Xu Wang

  3. School of International Relations and Public Affairs, Fudan University, Shanghai, 200433, People’s Republic of China

    Wu Zhu

  4. Guangxi Branch, Agricultural Bank of China, Nanning, 530028, People’s Republic of China

    Liang Chen

Authors
  1. Shuguang Zhao
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  2. Xu Wang
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  3. Liang Chen
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  4. Wu Zhu
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Corresponding author

Correspondence to Xu Wang.

Additional information

This paper was partially supported by National Natural Science Foundation of China (No. 61271114 and No. 61203325) and Innovation Program of Shanghai Municipal Education Commission (No. 14ZZ068).

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Zhao, S., Wang, X., Chen, L. et al. A Novel Self-adaptive Differential Evolution Algorithm with Population Size Adjustment Scheme. Arab J Sci Eng 39, 6149–6174 (2014). https://doi.org/10.1007/s13369-014-1248-7

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  • DOI: https://doi.org/10.1007/s13369-014-1248-7

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