Many problems addressed in operational research are combinatorial and NP-hard type. Therefore, designing binary algorithms based on swarm intelligence continuous metaheuris-tics is an area of interest in operational research. In this paper we use a general binarization mechanism based on the percentile concept. We apply the percentile concept to multi-verse optimizer algorithm to solve set covering problem (SCP). Experiments are designed to demonstrate the utility of the percentile concept in binarization. Additionally we verify the efficiency of our algorithm through benchmark instances, showing that Binary multi-verse Optimizer (BMVO) obtains adequate results when it is evaluated against another state of the art algorithm.
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