Yoshida and Adachi’s diploid genetic algorithm- the so-called pseudo-Meiosis genetic Algorithm (psM GA)- was focused on preserving population diversity and adapting the population quickly to problem changes. The large population diversity provided by psM GA with good adaptation to the problem changes were effective and sufficient to tackle non-stationary traveling salesman problem. They did not apply this genetic algorithm to other problem domains, like bit-coding problems. Hence, in this paper we revisit the psM GA, apply it on bit-coding problems so as to see the effect and search power of this genetic search algorithm on this problem domain.