基于改进量子遗传算法的Flow-Shop调度求解

针对Flow-Shop调度问题，提出一种改进的量子遗传算法，重点对量子变异和量子灾变等操作算子进行改进，提出局部量子位变异和局部量子灾变等操作算子。给出Flow-Shop调度问题的数学模型，提出了用量子遗传算法求解Flow-Shop调度问题的量子比特编码和解码方法，介绍算法的计算流程。仿真实验结果表明：改进的量子遗传算法具有收敛速度快、鲁棒性好等优点。

Design of Flow-shop by Using Improved Quantum Genetic Algorithm

Aiming at flow-shop scheduling problem, the paper proposes an improved quantum genetic algorithm, with emphasis on improving operators such as quantum mutation and catastrophe, describing a local quantum mutation and catastrophe. Mathematical model of flow-shop is presented in the paper, and the improved quantum genetic algorithm is used for solving the flow-shop scheduling problem, in which the qubit encoding and decoding is posed fit for the problem. Calculating steps are also given out. Though analyzing the simulation experiment, the results show that the improved quantum genetic algorithm is characterized by rapid convergence, excellent robustness and so on.