Publication – Implementation of Modified Talbi’s Quantum Inspired Genetic Algorithm for Travelling Salesman Problem on an IBM Quantum Computer

In this study, a Quantum-Inspired Genetic Algorithm is implemented on an IBM Quantum Computer and compared with a Classical Genetic Algorithm based on the Travelling Salesman Problem. Out of numerous Quantum-Inspired Algorithms, the ones which are designed based on the assumption that the qubit state can be duplicated to another variable without collapsing the state during its measurement are only designed for classical computers which is a blocker to be implemented on real Quantum devices. Also, the majority of the previous studies have been simulated on classical computers. Therefore, in this study a selected Quantum-Inspired Genetic Algorithm is initially executed on a high-performance IBM quantum simulator and a modified version of the algorithm is implemented on an IBM Quantum Computer. Both the original and the modified algorithms demonstrated stability during the simulation and on real Quantum devices. However, in any of the instances acceptable level of convergence was not seen when compared with a classical genetic algorithm. Yet this study is able to remove a blocker for Quantum-Inspired Algorithms to be implemented on real quantum computers. Also, to the best of our knowledge it is the first time for a quantum-inspired algorithm which is constrained with this design limitation to be implemented on a Quantum Computer.