中图分类号:
TP301.6
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参考文献
[1] Rahnamayan S, Wang G. Solving large scale optimization problems by opposition-based differential evolution[J]. WSEAS Transactions on Computers, 2008, 7(10):1792-1804.
[2] 黄光球, 李涛, 陆秋琴. 人工记忆优化算法[J]. 系统工程理论与实践, 2014, 34(11):2900-2912. Huang G Q, Li T, Lu Q Q. Artificial memory-based optimization[J]. Systems Engineering-Theory & Practice, 2014, 34(11):2900-2912.
[3] 张芳芳, 王建军, 张勇. 少控制参数的分层式骨干粒子群优化算法[J]. 系统工程理论与实践, 2015, 35(12):3217-3224. Zhang F F, Wang J J, Zhang Y. Layer bare-bones particle swarm optimization algorithm with few control parameters[J]. Systems Engineering-Theory & Practice, 2015, 35(12):3217-3224.
[4] Rao R, Savsani V, Vakharia D. Teaching-learning-based optimization:An optimization method for continuous nonlinear large scale problems[J]. Information Sciences, 2012, 183:1-15.
[5] Sayed E, Essam D, Sarker R, et al. Decomposition-based evolutionary algorithm for large scale constrained problems[J]. Information Sciences, 2015, 316:457-486.
[6] Tang D, Cai Y, Zhao J, et al. A quantum-behaved particle swarm optimization with memetic algorithm and memory for continuous non-linear large scale problems[J]. Information Sciences, 2014, 289:162-189.
[7] Ali M Z, Awad N H, Suganthan P N. Multi-population differential evolution with balanced ensemble of mutation strategies for large-scale global optimization[J]. Applied Soft Computing, 2015, 33:304-327.
[8] 黄光球, 赵魏娟, 陆秋琴. 求解大规模优化问题的可全局收敛蝙蝠算法[J]. 计算机应用研究, 2013, 30(5):1323-1328. Huang G Q, Zhao W J, Lu Q Q. Bat algorithm with global convergence for solving large scale optimization problem[J]. Application Research of Computers, 2013, 30(5):1323-1328.
[9] Mirjalili S, Lewis A. The whale optimization algorithm[J]. Advances in Engineering Software, 2016, 95:51-67.
[10] Watkins W A, Schevill W E. Aerial observation of feeding behavior in four baleen whales:Eubalaena glacialis, Balaenoptera borealis, Megaptera novaeangliae, and Balaenoptera physalus[J]. Journal of Mammalogy, 1979, 60(1):155-163.
[11] Haupt R, Haupt S. Practical genetic algorithm[M]. New York:John Wiley and Sons, 2004.
[12] Tizhoosh H R. Opposition-based learning:A new scheme for machine intelligence[C]//Proceedings of the IEEE International Conference on Intelligent Agents, Vienna, IEEE Press, 2005:695-701.
[13] Rahnamayan S, Tizhoosh H R, Sakama M A. Opposition-based differential evolution[J]. IEEE Transactions on Evolutionary Computation, 2008, 12(1):64-79.
[14] Wang H, Wu Z, Rahamayan S, et al. Enhancing particle swarm optimization using generalized opposition-based learning[J]. Information Sciences, 2011, 181(20):4699-4714.
[15] 周新宇, 吴志健, 王晖, 等. 一种精英反向学习的粒子群优化算法[J]. 电子学报, 2013, 41(8):1647-1652. Zhou X Y, Wu Z J, Wang H, et al. Elite opposition-based particle swarm optimization[J]. Acta Electronica Sinica, 2013, 41(8):1647-1652.
[16] 魏政磊, 赵辉, 李牧东, 等. 控制参数值非线性调整策略的灰狼优化算法[J]. 空军工程大学学报(自然科学版), 2016, 17(3):68-72. Wei Z L, Zhao H, Li M D, et al. A grey wolf optimization algorithm based on nonlinear adjustment strategy of control parameter[J]. Journal of Air Force Engineering University (Natural Science Edition), 2016, 17(3):68-72.
[17] Wang Y, Cai Z X, Zhou Y R, et al. Constrained optimization based on hybrid evolutionary algorithm and adaptive constraint-handling technique[J]. Structural and Multidisciplinary Optimization, 2009, 37(1):395-413.
[18] Engelbrecht A P. Fundamentals of computational swarm intelligence[M]. New York:John Wiley and Sons, 2004.
[19] Qin A K, Huang V L, Suganthan P N. Differential evolution algorithm with strategy adaptation for global numerical optimization[J]. IEEE Transactions on Evolutionary Computation, 2009, 13(2):398-417.
[20] Wang Y, Cai Z, Zhang Q. Differential evolution with composite trial vector generation strategies and control parameters[J]. IEEE Transactions on Evolutionary Computation, 2011, 15(1):55-66.
[21] Liang J, Qin A K, Suganthan P N, et al. Comprehensive learning particle swarm optimizer for global optimization of multimodal functions[J]. IEEE Transactions on Evolutionary Computation, 2006, 10(3):281-295.
[22] Igel C, Hansen N, Roth S. Covariance matrix adaptation for multi-objective optimization[J]. Evolutionary Computation, 2007, 15(1):1-28.
[23] Tou S, Zhang J, Yong L, et al. A harmony search algorithm for high-dimensional multimodal optimization problems[J]. Digital Signal Processing, 2015, 46:151-163.
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脚注
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基金
国家自然科学基金(61463009,61403046);贵州省科学技术基金(黔科合基础[2016]1022);商务部与贵州财经大学联合基金(2016SWBZD13);湖南省自然科学基金(2016JJ3079)
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