New Approach for Animal Migration Optimization Algorithm

Animal migration optimization has few limitations such as movement probability, limitations of certain factors for reproduction and limited growth of individuals. In this paper, we aim to propose an innovative approach for animal migration optimization which is being proposed for a better animal migration optimization that can work on multiple factors and will lead to a new algorithm that can work on multiple scenarios. An overview using a flow chart is given to explain the overview of the new proposed algorithm. The results have been calculated on four benchmark functions which show the enactment of the animal migration algorithm and its working. Mean standard deviation and global minima are factors which are calculated.

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