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首页> 外文期刊>International Journal of Computational Science and Engineering >IFOA: an improved forest algorithm for continuous nonlinear optimisation
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IFOA: an improved forest algorithm for continuous nonlinear optimisation

机译:IFOA:一种改进的连续非线性优化森林算法

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Forest optimisation algorithm (FOA) is a new evolutionary optimisation algorithm which is inspired by seed dispersal procedure in the forests, suitable for continuous nonlinear optimisation problems. In this paper, an improved forest optimisation algorithm (IFOA) is introduced to improve convergence speed and the accuracy of FOA, and four improvement strategies which include the greedy strategy, waveform step, preferential treatment of best tree and new-type global seeding are proposed to solve continuous nonlinear optimisation problems better. The capability of IFOA has been investigated through the performance of several experiments on well-known test problems and the results prove that IFOA is able to perform global optimisation effectively with high accuracy and convergence speed.
机译:森林优化算法(FOA)是一种新的进化优化算法,受森林中的种子分散程序的启发,适用于连续的非线性优化问题。 在本文中,引入了一种改进的森林优化算法(IFOA)以提高FOA的收敛速度和准确性,并提出了四种改进策略,包括贪婪策略,波形步骤,最佳树和新型全球播种的优先处理。 要更好地解决连续的非线性优化问题。 已经通过对众所周知的测试问题的几个实验进行了研究的能力,结果证明了IFOA能够以高精度和收敛速度有效地进行全局优化。

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