Migration Birds Algorithm (MBO) is a new optimization algorithm inspired by swarm intelligence.MBO was developed by Duman, Uysal and Alkaya in 2012. They applied it to solve quadratic assignmentproblem. Some recent studies demonstrate that MBO shows promising results for the problems incontinuous domain. Defining an effective neighborhood function is one of the most important phases inheuristic algorithms since it leads a more effective exploration of the solution space. With this motivation, inthis work, we analyze the effect of four different neighborhood functions on MBO algorithm. We appliedMBO algorithm to 5 different functions on continuous domain. Our contribution in this study is to usedifferent neighborhood functions for MBO. Experimental studies show that while generating neighborschanging all dimensions of the solutions and taking the information of the best solution gives betterperformance results.
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