A Percentile Transition Ranking Algorithm Applied to Binarization of Continuous Swarm Intelligence Metaheuristics

The binarization of continuous swarm-intelligence metaheuristics is an area of great interest in operational research. This interest is mainly due to the application of binarized metaheuristics to combinatorial problems. In this article we propose a general binarization algorithm called Percentil Transition Ranking Algorithm (PTRA). PTRA uses the percentile concept as a binarization mechanism. In particular we apply this mechanism to the Cuckoo Search metaheuristic to solve the Set Covering Problem (SCP). We provide necessary experiments to investigate the role of key ingredients of the algorithm. Finally to demonstrate the efficiency of our proposal, Set Covering benchmark instances of the literature show that PTRA competes with the state-of-the-art algorithms.