Quantum-behaved particle swarm optimization for solving job-shop scheduling problem

Dealing with such disadvantages of PSO algorithm as finite sampling space,being easy to run into prematurity,QPSO algorithm was proposed to be applied to solve job-shop scheduling problem(JSSP).During the scheduling process,obeying to some particular regulations,every scheduling was encoded into a matrix,and this matrix was regarded as a particle in QPSO algorithm;the objective function was determined based on the objective of scheduling.According to evolution formulae of QPSO algorithm,the scheduling space was searched for the global optimization.The simulation results show that this algorithm has better global convergence ability and more rapid convergence,and it is superior to genetic algorithm(GA) and PSO algorithm.