求解作业车间调度问题的混合QPSO算法

Hybrid QPSO algorithm for job shop scheduling problems

文章使用混合量子粒子群优化算法求解作业车间调度问题,并设计了一种基于工序的编码方式;为了克服量子粒子群优化算法容易陷入局部最优的缺点,将模拟退火算法引入量子粒子群优化算法,使算法具有跳出局部最优的能力并增强其全局搜索能力,形成量子粒子群-模拟退火调度算法;仿真结果表明,混合算法具有良好的全局收敛性能。

A hybrid quantum particle swarm optimization（QPSO） algorithm for the job shop scheduling problem is proposed and a coding method based on the order is designed in this paper. In order to resolve the flaw of the quantum particle swarm optimization algorithm that it is easily trapped into local optimization, the hybrid algorithm combines the QPSO algorithm and the simulated annealing algorithm so that it can escape from local optima, and its global search ability is also improved. The simulation results show that the hybrid algorithm has good global convergence ability.