Quantum-behaved Pigeon-inspired optimization Algorithm based on Particle-best Mutation

Aiming at the problem that the Quantum-behaved Pigeon-inspired optimization Algorithm is easy to fall into the local optimum and is lack of fine search ability, a new algorithm based on particle-best mutation is proposed. Firstly, aiming at the map and compass operator characteristics of solve rough search, Cauthy mutation based on particle-best was adopted for the pigeons when they have not evolved at this stage, so as to enhance the global search ability. Then, aiming at the landmark operator characteristics of solve fine search, Gaussian mutation after updating by landmark operator was adopted for the pigeons when they have not evolved at this stage, so as to enhance the local search ability. Finally, model of pigeons’ number factor which likes map and compass factor was built to keep the pigeons in the landmark operator at a certain amount, so as to get the optimal solution. The function test results show that the search speed and accuracy of the improved algorithm are better than other popular algorithms.