Résumé: This article develops an evolutionary nature inspired algorithm based on the social behavior of the goat, a pet of a farmer in a village life. In village life, we generally see the shepherds keep their goats free/untie from collar thread for grazing in the early morning and receives them at the end of the day when they come back into the home with their own efforts. But some day the goats did not come back in due time because of overfeeding of grass causing unable to move any more after meeting their grasp and began to get rest there. The shepherd feels more tempted and began to search for his/her goat. After untie, the goat began to graze herself through the walk on the path of the cultivated land and bank of the village ponds. The search process is going on through that path until it is not finally got. To characterize this problem some definitions like false walk, uniform and non-uniform steps, goat's jump, periodic walk and goodness of fit for various walk functions have been discussed here rigorously. Inspiring from this fact novel metaheuristic algorithms along with pseudocode and hardware specification have been discussed to optimize a benchmark multi-modal objective function having some singularity zones explicitly. Numerical results have been compared with some of the existing state- of -arts under 95% confidence intervals. Also, graphical illustrations are performed to validate the proposed approach. Finally, a conclusion is made followed by scope of future work

Langue: Anglais