Quantum artificial bee colony optimization algorithm based on Bloch coordinates of quantum bit
Kun Hou · Journal of Computer Applications · 2012
To solve the problems of slow convergence speed and easily getting into local optimal value for Artificial Bee Colony(ABC) algorithm,a new quantum optimization algorithm was proposed by combining quantum theory and artificial colony algorithm.This algorithm expanded the quantity of the global optimal solution and improved the probability of achieving the global optimal solution by using Bloch coordinates of quantum bit encoding food sources in the artificial colony algorithm;then food sources were updated by quantum rotation gate.This paper put forward a new method for determining the relationship between the two rotation phases in the quantum rotation gate.When the ABC algorithm searched as the equal area on the Bloch sphere,it was proved that the size of the two rotation phases in the quantum rotation gate approximated to the inverse proportion.This avoided blind arbitrary rotation and made the search regular when approaching the optimal solutions.The experiments of two typical optimization issues show that the algorithm is superior to the common Quantum Artificial Bee Colony(QABC) and the simple ABC in both search capability and optimization efficiency.