Abstract
Quantum-dot Cellular Automata (QCA) is prospective nanotechnology that has been named one of the top six upcoming computer technologies. QCA is a method for building computational systems that encode binary logics via the arrangement of charges among quantum dots. It is highly fast, has low power usage, and is extremely dense. QCA technology, in particular, brings up new possibilities for power savings and high-performance clock rates. Because of the appropriate properties, the execution of logic circuits utilizing QCA technology is a hotly debated topic. Design tools must handle many problems posed by QCA technology circuit design. Nature-inspired meta-heuristic algorithms play a vital role in computer processing, and algorithms with faster performance rates are more valuable. However, so far, there is no systematic study that regularly examines the role of nature-inspired met heuristic algorithms in QCA. Hence, the present investigation examines the applications of nature-inspired met heuristic algorithms in QCA. The articles on QCA optimization algorithms are selected and analyzed using the systematic literature review method. Also, important challenges and suggestions for future work are highlighted. The results showed that QCA-based digital logic circuits could be optimized using nature-inspired algorithms by reducing the number of gates.
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