首页> 外文会议>Proceedings of the 4th World Congress on Intelligent Control and Automation vol.4 >A Gradient-guided Niching Method in Genetic Algorithm for Solving Continuous Optimisation Problems
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A Gradient-guided Niching Method in Genetic Algorithm for Solving Continuous Optimisation Problems

机译:遗传算法中的梯度导引小生境法求解连续优化问题

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A hybrid genetic algorithm, which embeds a gradient-based local search route into a niching genetic algorithm, is proposed for solving continuous optimisation problems. The optimisation algorithm is applied to three nonlinear functions each having up to 100 variables and multi-minima. The test results show that relative to a standard niching algorithm the combination of a gradient-based search and niching improves the searching precision by several orders and the capability for locating the global optimum is significantly improved.
机译:为了解决连续优化问题,提出了一种混合遗传算法,该算法将基于梯度的局部搜索路径嵌入到适当的遗传算法中。优化算法应用于三个非线性函数,每个函数最多具有100个变量和多个最小值。测试结果表明,相对于标准的小生境算法,基于梯度的搜索和小生境的组合将搜索精度提高了几个数量级,并且全局最优定位的能力得到了显着提高。

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