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An improved design optimisation algorithm based on swarm intelligence

机译:一种基于群体智能的改进设计优化算法

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In design optimisation field, there are many non-linear optimisation problems and the traditional algorithms cannot deal with these problems well. In this paper, we improve the standard particle swarm optimisation (PSO) and propose a new algorithm to solve the overcome of standard PSO algorithm like being trapped easily into a local optimum. The new algorithm keeps not only the fast convergence speed characteristic of PSO, but effectively improves the capability of global searching as well. Compared with standard PSO on the benchmark functions, the results show that the new algorithm is efficient. We also used the new algorithm to solve design optimisation problems and the experiment results show the new algorithm is effective for these problems.
机译:在设计优化领域,存在很多非线性优化问题,传统算法不能很好地解决这些问题。在本文中,我们改进了标准粒子群算法(PSO),并提出了一种新的算法来解决标准PSO算法的难题,例如容易陷入局部最优中。新算法不仅保持了PSO的快速收敛速度特性,而且还有效地提高了全局搜索的能力。与基准函数上的标准PSO进行比较,结果表明该算法是有效的。我们还使用该新算法解决了设计优化问题,实验结果表明该新算法对这些问题有效。

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