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- W2128403012 abstract "organization systems are an increasingly attractive dynamic processes without a central control, emerge global order from local interactions in a bottom up approach. The advantage of blending the concept of self-organization enhances the working efficiency of other techniques to find a solution of huge search problem. Genetic Algorithms (GA) is such a technique, inspired by the natural evolution process, used to solve difficult optimization problem of large space solution, for an example, multiple sequence alignment (MSA) problem in a bioinformatics research. Self-organization technique automates the selection of appropriate parameter values of GA during execution without the user's intervention. An attempt towards applying Self-organizing Genetic Algorithm (SOGA) on MSA requires a complete knowledge of the various parameters of SO and its relationships. This lead us to make a complete survey on inherent properties of SO and the method of blending GA in order to develop a self-organizing genetic algorithm (SOGA) for MSA. The aim of the research is to make use of the efficiency of GA without getting any input from the non- trained users to tune the parameters in order to achieve the expected result." @default.
- W2128403012 created "2016-06-24" @default.
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- W2128403012 date "2013-03-15" @default.
- W2128403012 modified "2023-09-24" @default.
- W2128403012 title "Self-Organizing Genetic Algorithm: A Survey" @default.
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