參考文獻

[1] 辛斌，陳杰. 面向復(fù)雜優(yōu)化問題求解的智能優(yōu)化方法[M]. 北京：北京理工大學(xué)出版社，2018.

[2] AI B, DONG M G, JANG C X. Simple PSO algorithm with opposition-based learning average elite strategy[J]. International Journal of Hybrid Information Technology, 2016, 9(6): 187-196.

[3] 梁才浩，段獻忠. 分布式發(fā)電及其對電力系統(tǒng)的影響[J]. 電力系統(tǒng)自動化，2001, 25(12):53-56.

[4] 劉鎏. 多目標優(yōu)化進化算法及應(yīng)用研究[D]. 天津：天津大學(xué)，2009.

[5] 王勇，蔡自興，周育人，等. 約束優(yōu)化進化算法[J]. 軟件學(xué)報，2009, 20(1): 11-29.

[6] 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(4): 395-413.

[7] 童旅楊. 基于差分進化的智能優(yōu)化算法研究[D]. 桂林：桂林理工大學(xué)，2018.

[8] DAS S, SUGANTHAN P N. Differential evolution: a survey of the state-of-the-art[J]. IEEE Transactions on Evolutionary Computation, 2011, 15(1): 4-31.

[9] DAS S, MULLICK S S, SUGANTHAN P N. Recent advances in differential evolution-an updated survey[J]. Swarm and Evolutionary Computation, 2016(27): 1-30.

[10] DAS S, ABRAHAM A, CHAKRABORTY U K, et al. Differential evolution using a neighborhood-based mutation operator[J]. IEEE Transactions on Evolutionary Computation, 2009, 13(3): 526-553.

[11] 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.

[12] GONG W, CAI Z. Differential evolution with ranking-based mutation operators[J]. IEEE Transactions on Cybernetics, 2013, 43(6): 2066-2081.

[13] ZHANG J, SANDERSON A C. JADE: adaptive differential evolution with optional external archive[J]. IEEE Transactions on Evolutionary Computation, 2009, 13(5): 945-958.

[14] TANABE R, FUKUNAGA A. Success-history based parameter adaptation for differential evolution[C]// 2013 IEEE Congress on Evolutionary Computation, June 20-23, 2013, Cancun, Mexico. Piscataway: IEEE Press, 2013: 20-23.

[15] TANABE R, FUKUNAGA A S. Improving the search performance of SHADE using linear population size reduction[C]//2014 IEEE Congress on Evolutionary Computation (CEC), July 6-11, 2014, Beijing, China. Piscataway: IEEE Press, 2014.

[16] WU G, MALLIPEDDI R, SUGANTHAN P N, et al. Differential evolution with multi-population based ensemble of mutation strategies[J]. Information Sciences, 2016(329): 329-345.

[17] LIU X F, ZHAN Z H, ZHANG J. Dichotomy guided based parameter adaptation for differential evolution[C]//The 2015 Annual Conference on Genetic and Evolutionary Computation, July 11-15, 2015, Madrid, Spain. New York: ACM Press, 2015: 289-296.

[18] WANG H, WU Z, RAHNMAYAN S. Enhanced opposition-based differential evolution for solving high-dimensional continuous optimization problems[J]. Soft Computing, 2011, 15(11): 2127-2140.

[19] ZHONG J H, ZHANG J. Adaptive multi-objective differential evolution with stochastic coding strategy[C]//The 13th Annual Conference on Genetic and Evolutionary Computation, July 12-16, 2011, Dublin, Ireland. New York: ACM Press, 2011: 665-672.

[20] ALI M, SIARRY P, PANT M. An efficient differential evolution based algorithm for solving multi-objective optimization problems[J]. European Journal of Operational Research, 2012,217(2): 404-416.

[21] RAHNAMAYAN S, TIZHOOSH H R, SALAMA M M A. Opposition-based differential evolution[J]. IEEE Transactions on Evolutionary Computation, 2008, 12(1): 64-79.

[22] ZHANG Q, LI H. MOEA/D: a multiobjective evolutionary algorithm based on decomposition[J]. IEEE Transactions on Evolutionary Computation, 2007, 11(6): 712-731.

[23] ZHAO S Z, SUGANTHAN P N, ZHANG Q. Decomposition-based multiobjective evolutionary algorithm with an ensemble of neighborhood sizes[J]. IEEE Transactions on Evolutionary Computation, 2012, 16(3): 442-446.

[24] ZHANG Q, LIU W, LI H. The performance of a new version of MOEA/D on CEC09 unconstrained MOP test instances[C]//2009 IEEE Congress on Evolutionary Computation, May 18-21, 2009, Trondheim, Norway. Piscataway: IEEE Press, 2009.

[25] QU B Y, SUGANTHAN P N. Multi-objective differential evolution based on the summation of normalized objectives and improved selection method[C]//2011 IEEE Symposium on Dif ferential Evolution (SDE), April 11-15, 2011, Paris, France. Piscataway: IEEE Press, 2011.

[26] DENYSIUK R, COSTA L, ESPíRITO SANTO I. Many-objective optimization using differential evolution with variable-wise mutation restriction[C]//The 15th Annual Conference on Genetic and Evolutionary Computation, July 6-10, 2013, Amsterdam, The Netherlands. New York: ACM Press, 2013: 591-598.

[27] MALLIPEDDI R, SUGANTHAN P N. Ensemble of constraint handling techniques[J]. IEEE Transactions on Evolutionary Computation, 2010, 14(4): 561-579.

[28] GONG W, CAI Z, LIANG D. Adaptive ranking mutation operator based differential evolution for constrained optimization[J]. IEEE Transactions on Cybernetics, 2015, 45(4): 716-727.

[29] LIU H, CAI Z, WANG Y. Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization[J]. Applied Soft Computing, 2010,10(2): 629-640.

[30] SARDAR S, MAITY S, DAS S, et al. Constrained real parameter optimization with a gradient repair based differential evolution algorithm[C]//2011 IEEE Symposium on Differential Evolution(SDE), April 11-15, 2011, Paris, France. Piscataway: IEEE Press, 2011.

[31] WANG Y, CAI Z. Combining multiobjective optimization with differential evolution to solve constrained optimization problems[J]. IEEE Transactions on Evolutionary Computation, 2012,16(1): 117-134.

[32] SAHA C, DAS S, PAL K, et al. A fuzzy rule-based penalty function approach for constrained evolutionary optimization[J]. IEEE Transactions on Cybernetics, 2016, 46(12): 2953-2965.

[33] WU G, PEDRYCZ W, SUGANTHAN P N, et al. A variable reduction strategy for evolutionary algorithms handling equality constraints[J]. Applied Soft Computing, 2015(37): 774-786.

[34] PAN Q K, TASGETIREN M F, LIANG Y C. A discrete differential evolution algorithm for the permutation flowshop scheduling problem[J]. Computers & Industrial Engineering, 2008,55(4): 795-816.

[35] DAMAK N, JARBOUI B, SIARRY P, et al. Differential evolution for solving multi-mode resource-constrained project scheduling problems[J]. Computers & Operations Research, 2009, 36(9): 2653-2659.

[36] WANG L, PAN Q K, SUGANTHAN P N, et al. A novel hybrid discrete differential evolution algorithm for blocking flow shop scheduling problems[J]. Computers & Operations Research, 2010, 37(3): 509-520.

[37] PAN Q K, WANG L, GAO L, et al. An effective hybrid discrete differential evolution algorithm for the flow shop scheduling with intermediate buffers[J]. Information Sciences, 2011,181(3): 668-685.

[38] TASGETIREN M F, SUGANTHAN P N, PAN Q K. An ensemble of discrete differential evolution algorithms for solving the generalized traveling salesman problem[J]. Applied Mathematics and Computation, 2010, 215(9): 3356-3368.

[39] TASGETIREN M F, PAN Q K, LIANG Y C. A discrete differential evolution algorithm for the single machine total weighted tardiness problem with sequence dependent setup times[J]. Computers & Operations Research, 2009, 36(6): 1900-1915.

[40] 姚芳，羅家祥，胡躍明. 二維板材組包排樣問題的離散差分進化算法求解[J]. 計算機輔助設(shè)計與圖形學(xué)學(xué)報，2012, 24(3): 406-413.