First introduced in 1995, the Particle Swarm Optimization (PSO) algorithm offers a reliable and efficient solution to real-valued optimization problems. However, extending it to binary-valued problems proved challenging. This paper proposes a new Boolean version of the PSO technique based on a novel mutation strategy. By employing an innovative mutation mechanism in the velocity bitstring, the method enforces a minimum perturbation level, reduces the risk of premature convergence, and promotes broader global search. Several variations of the algorithm and parameter combinations are evaluated using 47 benchmark functions to derive the best-performing configuration, which is then compared with other population-based methods to demonstrate the effectiveness of the proposed algorithm. Finally, the technique is applied to an antenna array thinning problem for the design of a planar antenna array with certain specifications.
Zaharis et al. (Sun,) studied this question.