The design of robust continuous metaheuristic techniques to apply them to combinatorial problems is a line of research with great applied potential. There are two major challenges in this regard. The first is related to the fact that many of the problems addressed at an industrial level are of the combinatorial type and the second has to do with the fact that no lesser subset of these problems are of the NP-hard type. In this study, a binarization mechanism has been proposed for continuous swarm intelligence metaheuristics which uses the percentile concept to perform binarization. This percentile concept is applied to Whale’s optimization algorithm to solve the set coverage problem (SCP). To identify the contribution of the method, experiments were designed which are compared with a baseline. Additionally, the proposal is compared with recently published algorithms, using reference instances. The results indicate that the binary percentile whale (BPWH) algorithm obtains adequate results when it is evaluated with a combinatorial problem such as the SCP.