A Novel Method for Optimal Synthesis of Reversible Circuits using Metaheuristic Algorithms
Subject Areas :
Maryam Mahmoudi
1
*
,
Neda Ashrafi Khozani
2
,
Ali Ghaorbani
3
1 - Department of Computer Engineering, Mey.C., Islamic Azad University, Meymeh, Iran.
2 - Department of Computer Engineering, Mey.C., Islamic Azad University, Meymeh, Iran.
3 - Department of Computer Engineering, Mey.C., Islamic Azad University, Meymeh, Iran.
Keywords: Reversible circuits, Optimization, Metaheuristic algorithms.,
Abstract :
A reversible logic circuit is a circuit that consists of reversible gates, and there is a one-to-one correspondence between its inputs and outputs. These circuits have a unique input corresponding to each output, and information loss does not occur as a result. So far, many attempts have been made in the field of automatic synthesis of reversible circuits, especially with the help of knowledge engineering methods. In this research, the problem of automatic synthesis of reversible circuits was innovatively modeled into a multi-criteria optimization problem, and then a new combination of genetic and bat metaheuristic algorithms was presented to solve this optimization problem. The architecture of the proposed method encodes reversible circuits as chromosomes in the genetic algorithm and as positions in the bat algorithm. By automatically sharing populations between the two algorithms, the method exploits the global exploration ability of GA and the local exploitation capability of BA in a complementary manner. The proposed method outperforms each algorithm individually, especially in quantum cost and delay. For example, in the 2’s complement circuit, the quantum cost drops from 25 and 22 to 19, with the delay reduced to 12. In the full adder, garbage outputs decrease from 18 to 9, indicating significant improvement.
- Design an optimized method for the synthesis of reversible circuits.
- Enhancing the performance and reducing quantum cost using an advanced method of population sharing.
- Reducing synthesis time in comparison to state-of-the-art methods.
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