[1]
|
Qian Zhi-Rong, Fan Guang-Ju. Handbook of Refractory Matter. Beijing: Metallurgical Industry Press, 1995. 25-37 (钱之荣, 范广举. 耐火材料实用手册. 北京: 冶金工业出版社, 1995. 25-37)
|
[2]
|
Gu Li-De. Special Refractory Matter. Beijing: Metallurgical Industry Press, 2000. 150 (顾立德. 特种耐火材料. 北京: 冶金工业出版社, 2000. 150)
|
[3]
|
Hu Qing-Fu. Manufacture and Application of Magnesium Compound. Beijing: Chemical Industry Press, 2004. 35-40 (胡庆福. 镁化合物生产与应用. 北京: 化学工业出版社, 2004. 35-40)
|
[4]
|
Xue Feng, Gu Gen-Hua. The energy-saving way of magnesia production. Energy Conservation, 1996, (6): 44-46(薛丰, 顾根华. 电熔镁砂生产的节能途径. 节能, 1996, (6): 44-46
|
[5]
|
Wu Yong-Jian, Zhang Li, Yue Heng, Chai Tian-You. Intelligent optimal control based on CBR for fused magnesia production. Journal of Chemical Industry and Engineering, 2008, 59(7): 1686-1690 (吴永建, 张莉, 岳恒, 柴天佑. 基于案例推理的电熔镁炉智能优化控制. 化工学报, 2008, 59(7): 1686-1690)
|
[6]
|
Wu Z W, Chai T Y, Fu J, Sun J. Hybrid intelligent optimal control of fused magnesium furnaces. In: Proceedings of the 49th IEEE Conference on Decision and Control. Atlanta, GA, USA: IEEE, 2010. 3313-3318
|
[7]
|
Wu Zhi-Wei, Chai Tian-You, Fu Jun, Yan Zhan-Wei. Intelligent setpoints control of smelting process of fused magnesium furnace. Control and Decision, 2011, 26(9): 1417-1420 (吴志伟, 柴天佑, 付俊, 闫占伟. 电熔镁炉熔炼过程的智能设定值控制. 控制与决策, 2011, 26(9): 1417-1420)
|
[8]
|
Kong W J, Chai T Y, Yang S X, Ding J J. A hybrid evolutionary multiobjective optimization strategy for the dynamic power supply problem in magnesia grain manufacturing. Applied Soft Computing Journal, 2013, 13(5): 2960-2969
|
[9]
|
Wiesemann W, Kuhn D, Rustem B. Multi-resource allocation in stochastic project scheduling. Annals of Operations Research, 2012, 193(1): 193-220
|
[10]
|
Su Zhao-Pin, Jiang Jian-Guo, Liang Chang-Yong, Zhang Guo-Fu. A distributed algorithm for parallel multi-task allocation based on profit sharing learning. Acta Automatica Sinica, 2011, 37(7): 865-872
|
[11]
|
Zhou Wei, He Jian-Min, Yu De-Jian. Traffic flow hidden measure and assignment model for the uncertain direction military traffic network. Acta Automatica Sinica, 2012, 38(2): 315-320 (周伟, 何建敏, 余德建. 非定向军事路网交通流隐蔽性测度及分配模型. 自动化学报, 2012, 38(2): 315-320)
|
[12]
|
Cheng T C E, Lin B M T, Huang H L. Resource-constrained flowshop scheduling with separate resource recycling operations. Computers and Operations Research, 2012, 39(6): 1206-1212
|
[13]
|
Riera-Ledesma J, Salazar-González J J. A column generation approach for a school bus routing problem with resource constraints. Computers and Operations Research, 2013, 40(2): 566-583
|
[14]
|
Solimanpur M, Sattari H, Abazari A M. Optimum process plan selection via branch-and-bound algorithm in an automated manufacturing environment. International Journal of Operational Research, 2012, 13(3): 281-294
|
[15]
|
Chen Jie, Chen Chen, Zhang Juan, Xin Bin. Deployment optimization for point air defense based on memetic algorithm. Acta Automatica Sinica, 2010, 36(2): 242-248 (陈杰, 陈晨, 张娟, 辛斌. 基于Memetic算法的要地防空优化部署方法. 自动化学报, 2010, 36(2): 242-248)
|
[16]
|
Gong Y J, Zhang J, Chung H S H, Chen W N, Zhan Z H, Li Y, Shi Y H. An efficient resource allocation scheme using particle swarm optimization. IEEE Transactions on Evolutionary Computation, 2012, 16(6): 801-816
|
[17]
|
Lin C M, Gen M. Multiobjective resource allocation problem by multistage decision-based hybrid genetic algorithm. Applied Mathematics and Computation, 2007, 187(2): 574-583
|
[18]
|
Yin P Y, Yu S S, Wang P P, Wang Y T. Multi-objective task allocation in distributed computing systems by hybrid particle swarm optimization. Applied Mathematics and Computation, 2007, 184(2): 407-420
|
[19]
|
Kennedy J, Eberhart R C. Particle swarm optimization. In: Proceedings of the 1995 IEEE International Conference on Neural Networks. Piscataway, NJ: IEEE, 1995. 1942-1948
|
[20]
|
Eberhart R C, Shi Y H, Kennedy J. Swarm Intelligence. San Francisco: Morgan Kaufmann Publishers, 2001
|
[21]
|
Navalertporn T, Afzulpurkar N V. Optimization of tile manufacturing process using particle swarm optimization. Swarm and Evolutionary Computation, 2011, 1(2): 97-109
|
[22]
|
Coello C A C, Van Veldhuisen D A, Lamont G B. Evolutionary Algorithms for Solving Multi-Objective Problems. New York: Kluwer Academic Publishers, 2002
|
[23]
|
Coello C A C, Pulido G T, Lechuga M S. Handling multiple objectives with particle swarm optimization. IEEE Transactions on Evolutionary Computation, 2004, 8(3): 256-279
|
[24]
|
Knowles J, Corne D W. Approximating the nondominated front using the Pareto archived evolution strategy. Evolutionary Computation, 2000, 8(2): 149-172
|
[25]
|
Hu Guang-Hao, Mao Zhi-Zhong, He Da-Kuo. Multi-objective PSO optimization algorithm based on two stages-guided. Control and Decision, 2010, 25(3): 404-415 (胡广浩, 毛志忠, 何大阔. 基于两阶段领导的多目标粒子群优化算法. 控制与决策, 2010, 25(3): 404-415)
|
[26]
|
Mostaghim S, Teich J. Strategies for finding good local guides in multi-objective particle swarm optimization (MOPSO). In: Proceedings of the 2003 IEEE Swarm Intelligence Symposium. Indianapolis, Indiana, USA: IEEE, 2003. 26-33
|
[27]
|
Jia Shu-Jin, Du Bin, Yue Heng. Local search and hybrid diversity strategy based multi-objective particle swarm optimization algorithm. Control and Decision, 2012, 27(6): 813 -826 (贾树晋, 杜斌, 岳恒. 基于局部搜索与混合多样性策略的多目标粒子群算法. 控制与决策, 2012, 27(6): 813-826)
|
[28]
|
Zhang Y, Gong D W, Ding Z H. A bare-bones multi-objective particle swarm optimization algorithm for environmental/economic dispatch. Information Science, 2012, 192: 213-227
|
[29]
|
Deb K, Pratap A, Agarwal S, Meyrivan T. A fast and elitist multiobjective genetic algorithm: NSGA-Ⅱ. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182-197
|
[30]
|
Ikesue A, Yoshitomi J, Shikano H. Dynamic wearing test for magnesia-carbon refractories using induction furnace. Tetsu-to-Hagané, 1991, 77(3): 391-397
|
[31]
|
Suykens J A K, Vandewalle J. Least squares support vector machine classifiers. Neural Processing Letters, 1999, 9(3): 293-300
|
[32]
|
Kong W J, Cheng W J, Ding J L, Chai T Y. A reliable and efficient hybrid PSO for parameters optimization of LS-SVM in production rate prediction. In: Proceedings of the 2010 International Symposium on Computational Intelligence and Design. Hangzhou, China: IEEE, 2010. 140-143
|
[33]
|
Qin Qin, Yue Qiang, Gu Gen-Hua, Guo Mao-Xian. DC submerged-arc furnace with twin electrodes for the fused magnesia production. Journal of Northeastern University (Natural Science), 2003, 24(7): 685-687 (秦勤, 岳强, 顾根华, 郭茂先. 双电极直流电熔镁埋弧电弧炉. 东北大学学报 (自然科学版), 2003, 24(7): 685-687)
|
[34]
|
Zitzler E, Thiele L. Multiobjective evolutionary algorithms: a comparative case study and the strength pareto approach. IEEE Transactions on Evolutionary Computation, 1999, 3(4): 257-271
|
[35]
|
Deb K, Thiele L, Laumanns M, Zitzler E. Scalable Test Problems for Evolutionary Multiobjective Optimization, Technical Report TIK-Report No. 112, Computer Engineering and Networks Laboratory (TIK), Swiss Federal Institute of Technology (ETH) Zurich, 2001
|
[36]
|
Zitzler E, Deb K, Thiele L. Comparison of multiobjective evolutionary algorithms: empirical results. Evolutionary Computation, 2000, 8(2): 173-195
|
[37]
|
Schott J R. Fault Tolerant Design Using Single and Multicriteria Genetic Algorithm Optimization[Master dissertation], Massachusetts Institute of Technology, UK, 1995
|