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首页> 外文期刊>Journal of Computers >Modified Shuffled Frog-leaping Algorithm with Dimension by Dimension Improvement
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Modified Shuffled Frog-leaping Algorithm with Dimension by Dimension Improvement

机译：修改后尺寸改进的混合青蛙跨越算法

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—Shuffled leap frog algorithm (SFLA) is a new nature-inspired intelligent algorithm, which uses the whole update and evaluation strategy on solutions. For solving multi-dimension function optimization problems, this strategy will deteriorate the convergence speed and the quality of solution of algorithm due to interference phenomena among dimensions. To overcome this shortage, a dimension by dimension improvement based on SFLA is proposed. The proposed strategy combines an updated value of one dimension with values of other dimensions into a new solution, and that whose updated value can improve the solution will be accepted greedily. Further, a new individual update formula is designed to learn experiences both from the global best and the local best solution simultaneously. Meanwhile, they also reveal the modified algorithm is competitive for continuous function optimization problems compared with other improved algorithms.
机译：-SheShubled Leap Frog算法（SFLA）是一种新的自然启发智能算法，它利用解决方案的整个更新和评估策略。为了解决多维功能优化问题，由于尺寸之间的干扰现象，这种策略将恶化算法的收敛速度和算法解决的质量。为了克服这种短缺，提出了基于SFLA的维度改善的维度。该策略将一个维度的更新值与其他维度的值相结合到新的解决方案中，并且其更新值可以改善解决方案将被贪婪地接受。此外，新的单独更新公式旨在从全球最佳和本地最佳解决方案同时学习体验。同时，与其他改进的算法相比，它们还揭示了改进的算法对连续功能优化问题具有竞争力。

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