A Retroactive Quantum-inspired Evolutionary Algorithm

This study outlines some weaknesses of existing Quantum-inspired Evolutionary Algorithms (QEA) by explaining how a bad choice of the rotation angle of qubit quantum gates can slow down optimal solutions discovery. A new algorithm, called Retroactive Quantum inspired Evolutionary Algorithm (rQEA), is proposed. With rQEA the rotation of individual’s amplitudes is performed by quantum gates according to a retroactive strategy making the algorithm more adaptive and thus leading to a good balance between intensification and diversification. Our algorithm was tested and compared to Classical Genetic Algorithm (CGA) and to QEA on two benchmark problems. Experiments have shown that rQEA performs better than both CGA and QEA in terms of genericity, adaptability and accuracy.