A Percentile Multi-Verse Optimizer Algorithm applied to the Knapsack problem

Abstract

Many problems addressed in operational research are combinatorial and NP-hard type. Therefore, designing binary algorithms based on swarm intelligence continuous metaheuristics 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 multiverse optimizer algorithm to solve multidimensional knapsack problem (MKP). 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.