Abstract

Animal Migration Optimization algorithm is stimulated by intelligent conduct of animal while migrating from one place to other place in search of food and secure habitat. This algorithm simulate the behavior of animal that how they shift from existing location to fresh location and how a number of animal depart from the group and other connect with the group. There are mainly two phases namely migration and population update. This paper presents a new strategy for population update in animal migration optimization algorithm using levy flight search strategy. The newly proposed strategy named as Levy Flight Animal Migration Optimization (LAMO) algorithm. The performance of LAMO tested over 21 bench mark functions and results compared with basic AMO algorithm so as to prove its reliability, robustness and efficiency.

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