Structural health monitoring (SHM) provides periodic observation of structures, which allows them to detect potential problems and analyze their state. The efficiency of SHM systems is highly dependent on the location and number of sensors. The use of a low number of sensors may result in data not being obtained with sufficient accuracy. In addition, the use of insufficient sensors may reduce the reliability of the SHM system. The use of too many sensors is not cost-effective and may increase the amount of data to be processed. With the increasing data volume, the evaluation time of the data may be longer. In this study, a new metaphor-free optimization algorithms, the best-mean-random (BMR) and best–worst-random (BWR) algorithms, are used to find the optimum number and location of sensors to be placed in a 20-storey, 460-member space frame system. During the optimization process, a computer program was developed that allows data transfer between SAP2000 and MATLAB via SAP2000-OAPI. According to the results, thanks to this computer program, the number of sensors can be selected without the need for experience, and with these algorithms, optimum sensor placements can be obtained with less processing volume. In addition, both algorithms reached the same number of sensors. Compared to the BMR method, the BWR algorithm reached the best result faster.