A quantum-inspired vortex search algorithm with application to function optimization

The vortex search is proposed as a new optimization algorithm recently. This algorithm has the advantages of simple operation and strong search capabilities. By introducing quantum computing into this algorithm, A quantum-inspired vortex search algorithm is presented in this paper. The initial population of the algorithm has only one individual called vortex center. First this individual is encoded by qubits described on the Bloch sphere, and then by repeatedly rotating all qubits on this individual about the same coordinate axis through random angles, some new individuals are generated. By choosing the best individual as a new vortex center, and rotating it again until meeting the termination conditions, the global optimal solution can be obtained. As the search in each dimension is carried out on the Bloch sphere, thus it is helpful to enhance the diversity of candidate solutions and inhibit premature convergence in the late stages of the algorithm. That the proposed algorithm is superior to the original one is demonstrated by the experimental results of some benchmark functions extreme optimization.