  Distributed quantum computing has been well-known for many years as a system
composed of a number of small-capacity quantum circuits. Limitations in the
capacity of monolithic quantum computing systems can be overcome by using
distributed quantum systems which communicate with each other through known
communication links. In our previous study, an algorithm with an exponential
complexity was proposed to optimize the number of qubit teleportations required
for the communications between two partitions of a distributed quantum circuit.
In this work, a genetic algorithm is used to solve the optimization problem in
a more efficient way. The results are compared with the previous study and we
show that our approach works almost the same with a remarkable speed-up.
Moreover, the comparison of the proposed approach based on GA with a random
search over the search space verifies the effectiveness of GA.
