4.7 Article

Hybrid Niching-Based Differential Evolution With Two Archives for Nonlinear Equation System

Journal

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
Volume 52, Issue 12, Pages 7469-7481

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMC.2022.3157816

Keywords

Optimization; Statistics; Sociology; Genetic algorithms; Convergence; Task analysis; Nonlinear equations; Archive; crowding; differential evolution (DE); nonlinear equations system (NES); speciation

Funding

  1. National Natural Science Foundation of China [62076225, 62073300]
  2. Natural Science Foundation for Distinguished Young Scholars of Hubei [2019CFA081]

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This article proposes a hybrid niching-based differential evolution algorithm with two archives, HNDE/2A, for locating multiple roots of nonlinear equation systems within a limited computational budget. By combining the techniques of crowding and speciation, as well as utilizing a root archive and an inferior offspring archive, the algorithm achieves better results in terms of root ratio and success rate compared to other algorithms.
Nonlinear equation systems (NESs) are ubiquitous, and solving them is an important yet challenging task in numerical computation. Most of the NESs usually contain multiple roots. To locate multiple roots, the use of evolutionary algorithms attracts more attention recently. For the purpose of finding different roots within a limited computational budget in a single run simultaneously, in this article, a hybrid niching-based differential evolution with two archives, referred to as HNDE/2A, is proposed. It can be featured as: 1) two niching techniques, i.e., crowding and speciation, are combined to balance the diversity and convergence; 2) a root archive is used to save the found roots during the run. Additionally, if a root is saved into the root archive, it will be reinitialized immediately to further promote the population diversity; and 3) an inferior offspring archive is presented to utilize the useful information of the inferior offspring. To evaluate the performance of our proposal, 30 problems are chosen as the test suite. Moreover, HNDE/2A is also used to solve two real-world problems. Compared with other algorithms, HNDE/2A yields better results in terms of the root ratio and the success rate with a less computational budget.

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