One Improved Discrete Particle Swarm Optimization Based on Quantum Evolution Concept
Xuyuan Li, XU Hua-long, Zhaogang Cheng · 2008
In order to solve the combinatorial optimization problem effectively, one improved discrete particle swarm optimization based on quantum evolution concept is proposed in the paper. Firstly, The quantum angle is defined and it is restricted in the range from -pi/2 to 0. Secondly, a new velocity update is proposed, it can update adaptively and can avoid the local optima. Thirdly, under the thought of quantum evolution, the particle can be transferred from decimal code to binary code, so the algorithm can be used to solve the discrete problem. From the experiment, we can learn that the algorithm can realize global optima effectively.