No / This paper proposes an approximate optimization approach, called QEAM, which combines a P system with active membranes and a quantum-inspired evolutionary algorithm. QEAM uses the hierarchical arrangement of the compartments and developmental rules of a P system with active membranes, and the objects consisting of quantum-inspired bit individuals, a probabilistic observation and the evolutionary rules designed with quantum-inspired gates to specify the membrane algorithms. A large number of experiments carried out on benchmark instances of satisfiability problem show that QEAM outperforms QEPS (quantum-inspired evolutionary algorithm based on P systems) and its counterpart quantum-inspired evolutionary algorithm.