[1]张建明.基于改进量子进化算法的作业车间调度研究[J].浙江理工大学学报,2014,31-32(自科3):310-315.
　ZHANG Jian ming.A Novel Quantum Evolutionary Algorithm for Job shop Scheduling[J].Journal of Zhejiang Sci-Tech University,2014,31-32(自科3):310-315.

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基于改进量子进化算法的作业车间调度研究()

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参考文献/References:

［1］ Narayanan A, Moore M. Quantum inspired genetic algorithm［C］//IEEE International Conference on Evolutionary Computation. Iscataway, 1996: 61-66.
［2］ Han K H, Kim J H. Genetic quantum algorithm and its application to combinatorial optimization problem［C］//IEEE International Conference on Evolutionary Computation. Lajolla, 2000: 1354-1360.
［3］ Han K H, Kim J H. Quantum inspired evolutionary algorithm for a class of combinatorial timization［J］. IEEE Transactions on Evolutionary Computation, 2002, 6(6): 580-593.
［4］ 杨俊安, 庄镇泉, 史亮. 多宇宙并行量子遗传算法［J］. 电子学报, 2004, 32(6): 923-928.
［5］ Zhang G, Gu Y, Hu L, et al. A novel quantum genetic algorithm and its application to digital filter design［J］. Intelligent Transportation Systems, 2003, 2: 1600-1605.
［6］ Chen H, Zhang J H, Zhang C. Chaos updating rotated gates quantuminspired genetic algorithm proceedings of the international conference on communications［J］. Cuircuits and Systems, 2004, 2: 1108-1112.
［7］ Wang L, Tang F, Wu H. Hybrid genetic algorithm based on quantum computing for numerical optimization and parameter estimation［J］. Appl Math Comput, 2005, 171: 1141-1156.
［8］ Li P, Li S. Quantuminspired evolutionary algorithm for continuous spaces optimization［J］. Chinese Journal of Electronics, 2008, 17(1): 80-84.
［9］ 李士勇, 李盼池. 基于实数编码和目标函数梯度的量子遗传算法［J］. 哈尔滨工业大学学报, 2006, 38(8): 1216-1218, 1223.
［10］ Li P, Li S. Quantum inspired evolutionary algorithm for continuous spaces optimization based on Bloch coordinates of qubits［J］. Neurocomputing, 2008, 72: 581-591.
［11］ Gu J, Gu X, Gu M. A novel parallel quantum genetic algorithm for stochastic job shop scheduling［J］. J Math Anal Appl, 2009, 355(1): 63-81.
［12］ Gu J, Gu M, Cao C, et al. A novel competitive co evolutionary quantum genetic algorithm for stochastic job shop scheduling problem［J］. Comput Oper Res, 2010, 37(5): 927-937.
［13］ 张建明. 基于改进量子进化算法的生产调度问题研究［D］. 上海: 华东理工大学, 2013.
［14］ Ripon K S N, Sam K, Man K F. A real coding jumping gene genetic algorithm (RJGGA) for multiobjective optimization［J］. Inf Sci, 2007, 177(2): 632-654.
［15］ Muth J F, Thompson G L. Industrial Scheduling［M］. EngleWood Cliffs: PrenticeHall, 1963.
［16］ Ripon K S N, Chi H T, Sam K. Multi objective evolutionary job shop scheduling using jumping genes genetic algorithm［C］//2006 International Joint Conference on Neural Networks. Vancouver, 2006: 3100-3107.
［17］ Gao L, Zhang G, Zhang L, et al. An efficient memetic algorithm for solving the job shop scheduling problem［J］. Comput Indust Engin, 2011, 60: 699-705.
［18］ Ombuki B M, Ventresca M. Local search genetic algorithms for job shop scheduling problem［J］. Applied Intelligence, 2004, 21: 99-109.
［19］ Nakano R, Yamada T. Conventional genetic algorithm for job shop problems［C］//Proceedings of the 4th International Conference on Genetic Algorithms (ICGA91). San Diego, 1991: 474-479.
［20］ Kennedy J, Eberhart R C. Particle swarm optimization［C］//IEEE International Conference on Neural Networks, Perth, 1995: 1942-1948.
［21］ Tasgetiren M F, Sevkli M, Liang Y C. A particle swarm optimization and differential evolution algorithms for job shop scheduling problem［J］. Inter J Oper Res, 2006, 3(2): 120-135.