Low Power State Assignments by Quantum-based Genetic Algorithm

Various circuit products have been applied wider and deeper in areas in the life, but unfortunately, the power/battery technologies cannot keep up with the development of the circuit. A low power circuit with ingenious design is one of the most important considerations of the engineers, as well as the researchers. Nowadays, the low power sequential circuit is the key to circuit design, which requires an elaborate state assignment that could be synthesized as a circuit of low energy consumption and small size. That comes to a multi-objective optimization. This paper applies both the Single-gene mutation and the full gene mutation operation in seeking the optimal solution; moreover, it combines the Quantum computing with the multi-objective Genetic Algorithm to achieve an ideal assignment effectively. The experiment results show that genetic algorithm methods are more superior to others in terms of the sensitivity of original solutions and the dependency of original parameters.