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Properties of robust solution searching in multi-dimensional space with genetic algorithms

机译:遗传算法在多维空间中搜索鲁棒解决的特性

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A large number of studies on genetic algorithms (GAs) emphasize finding a globally optimal solution. Some other investigations have also been made for detecting multiple solutions. If a global optimal solution is very sensitive to noise or perturbations in the environment then there may be cases where it is not good to use this solution. We have proposed a new scheme, GA/RS/sup 3/, which extends the application of GAs to domains that require the discovery of robust solutions and a mathematical model for this scheme has been developed restricting their search space to one-dimensional. We analyze properties of GAs/RS/sup 3/ in multi-dimension search spaces. The effectiveness of the scheme is demonstrated by solving two-dimensional functions having broad and sharp peaks.
机译:关于遗传算法(气体)的大量研究强调找到全球最佳解决方案。还对检测多种解决方案进行了一些其他调查。如果全局最佳解决方案对环境中的噪声或扰动非常敏感,则可能存在使用此解决方案的情况下不好。我们提出了一种新的计划,GA / RS / SUP 3 /,它扩展了需要发现强大的解决方案的域以及该方案的数学模型的应用程序,已经开发了他们的搜索空间到一维。我们分析了多维搜索空间中的气体/ RS / SUP 3 /中的性质。通过求解具有宽且尖峰峰的二维函数来证明该方案的有效性。

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