An Improved Version of opt-aiNet Algorithm (I-opt-aiNet) for Function Optimization
نویسندگان
چکیده
This paper presents an improved version of opt-aiNet, which is an algorithm for multimodal function optimization based on the natural immune system metaphor. The proposed algorithm has some major and minor changes on the way the clonal selection principle is applied within the original opt-aiNet algorithm which allows for fast localization of the optima. The output of the proposed algorithm is tested on the same data as the original opt-aiNet and the results show the validity of the new improved one.
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Verifying the published results of algorithms is part of the usual research process. This helps to both validate the existing literature, but also quite often allows for new insights and augmentations of current systems in a methodological manner. This is very pertinent in emerging new areas such as Artificial Immune Systems, where it is essential that any algorithm is well understood and inves...
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Verifying the published results of algorithms is part of the usual research process. This helps to both validate the existing literature, but also quite often allows for new insights and augmentations of current systems in a methodological manner. This is very pertinent in emerging new areas such as Artificial Immune Systems, where it is essential that any algorithm is well understood and inves...
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