改进的粒子群算法在轧制负荷分配中的优化
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摘要
针对带钢热连轧精轧机组中负荷分配的优化问题,提出一种基于经验的自适应双层粒子群优化算法(ADLPSO-EM)。每次种群迭代后,对记忆群体通过改进的更新公式进行更新。利用改进的自适应调整惯性权重的策略充分增强种群的多样性,提高全局搜索能力。最后,在将其应用于热连轧负荷分配问题时,通过以经验法得到的值产生一个搜索邻域,并通过变邻域求出最后的负荷分配。仿真结果表明,改进的算法对负荷分配优化具有明显的效果。
Aiming at the load distribution problem of hot strip rolling,an adaptive double layer particle swarm optimization algorithm based on empirical method(ADLPSO-EM)was proposed.After each population iteration,the algorithm uses improved speed update formula to update memory swarm.At the same time,in order to improve the diversity of the population,it uses an improved adaptive adjustment strategy to update inertia weight.Finally,The initialization section of the algorithm is a changeable neighborhood based on the value obtained by the empirical method in load distribution problem.The experimental results show that the improved algorithm has a significant effect on the load distribution optimization.
Aiming at the load distribution problem of hot strip rolling,an adaptive double layer particle swarm optimization algorithm based on empirical method(ADLPSO-EM)was proposed.After each population iteration,the algorithm uses improved speed update formula to update memory swarm.At the same time,in order to improve the diversity of the population,it uses an improved adaptive adjustment strategy to update inertia weight.Finally,The initialization section of the algorithm is a changeable neighborhood based on the value obtained by the empirical method in load distribution problem.The experimental results show that the improved algorithm has a significant effect on the load distribution optimization.
引文
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[13]WEI H L,ISA N A M.Two-layer particle swarm optimization with intelligent division of labor[J].Engineering Applications of Artificial Intelligence,2013,26(10):2327-2348.
[14]EPITROPAKISA M G,PLAGIANAKOS V P,VRAHATIS M N.Evolving cognitive and social experience in Particle Swarm Optimization through Differential Evolution:A hybrid approach[J].Information Sciences,2012,216(24):50-92.
[15]WEI H L,ISA N A M.An adaptive two-layer particle swarm optimization with elitist learning strategy[J].Information Sciences,2014,273(3):49-72.
[16]SHI Y,EBERHART R C.A Modified Particle Swarm Optimizer[C]∥Proceedings of the IEEE Conference on Evolutionary Computation.Piscataway,1998:69-73.
[17]ZHAN Z,ZHANG J,LI Y.Adaptive particle swarm optimization[J].IEEE Transactions on Systems,Man,Cybernetics B:Cybernetics,2009,39(6):1362-1381.
[18]WANG Y,LIU J L,SUN Y K.Immune Genetic Algorithms(IGA)Based Scheduling Optimization[J].Journal of University of Science and Technology Beijing,2002,24(3):339-341.(in Chinese)王焱,刘景录,孙一康.免疫遗传算法对精轧机组负荷分配的优化[J].北京科技大学学报,2002,24(3):339-341.
[2]LI H J,XU J Z,WANG G D.Improvement on conventional load distribution algorithm in hot tandem mills[J].Journal of Iron and Steel Research,International,2007,14(2):36-41.
[3]KENNEDY J,EBERHART R C.Particle Swarm Optimization[C]∥IEEE International Conference on Neural Networks.Piscataway,1995:1942-1948.
[4]KHARE A,RANGNEKAR S.A review of particle swarm optimization and its applications in Solar Photovoltaic system[J].Applied Soft Computing,2013,12(5):2997-3006.
[5]SUN J,PALADE V,WU X J,et al.Solving the Power Economic Dispatch Problem With Generator Constraints by Random Drift Particle Swarm Optimization[J].IEEE Transactions on Industrial Informatics,2014,10(1):222-232.
[6]HO S Y,LIN H S,LIAUH W H,et al.OPSO:Orthogonal Particle Swarm Optimization and Its Application to Task Assignment Problems[J].IEEE Transactions on Systems Man and Cybernetics Part A:Systems and Humans,2008,38(2):288-298.
[7]FU Y G,DING M Y,ZHOU C P.Phase Angle-Encoded and Quantum-Behaved Particle Swarm Optimization Applied to Three-Dimensional Route Planning for UAV[J].IEEE Transactions on Systems Man and Cybernetics Part A:Systems and Humans,2012,42(2):511-526.
[8]GONG Y J,SHEN M,ZHANG J.Optimizing RFID Network Planning by Using a Particle Swarm Optimization Algorithm with Redundant Reader Elimination[J].IEEE Transactions on Industrial Informatics,2012,8(4):900-912.
[9]LI C,YANG S,NGUYEN T T.A self-learning particle swarm optimizer for global optimization problems[J].IEEE Transactions on Systems Man and Cybernetics Part B Cybernetics,2012,42(3):627-646.
[10]WEI H L,ISA N A M.An adaptive two-layer particle swarm optimization with elitist learning strategy[J].Information Sciences,2014,273(3):49-72.
[11]CHEN W N,ZHANG J,LIN Y,et al.Particle Swarm Optimization With an Aging Leader and Challengers[J].IEEE Transactions on Evolutionary Computation,2013,17(2):241-258.
[12]HAN J H,LI Z R,WEI Z C.Adaptive Particle Swarm Optimization Algorithm and Simulation[J].Journal of System Simulation,2006,18(10):2969-2971.(in Chinese)韩江洪,李正荣,魏振春.一种自适应粒子群优化算法及其仿真研究[J].系统仿真学报,2006,18(10):2969-2971.
[13]WEI H L,ISA N A M.Two-layer particle swarm optimization with intelligent division of labor[J].Engineering Applications of Artificial Intelligence,2013,26(10):2327-2348.
[14]EPITROPAKISA M G,PLAGIANAKOS V P,VRAHATIS M N.Evolving cognitive and social experience in Particle Swarm Optimization through Differential Evolution:A hybrid approach[J].Information Sciences,2012,216(24):50-92.
[15]WEI H L,ISA N A M.An adaptive two-layer particle swarm optimization with elitist learning strategy[J].Information Sciences,2014,273(3):49-72.
[16]SHI Y,EBERHART R C.A Modified Particle Swarm Optimizer[C]∥Proceedings of the IEEE Conference on Evolutionary Computation.Piscataway,1998:69-73.
[17]ZHAN Z,ZHANG J,LI Y.Adaptive particle swarm optimization[J].IEEE Transactions on Systems,Man,Cybernetics B:Cybernetics,2009,39(6):1362-1381.
[18]WANG Y,LIU J L,SUN Y K.Immune Genetic Algorithms(IGA)Based Scheduling Optimization[J].Journal of University of Science and Technology Beijing,2002,24(3):339-341.(in Chinese)王焱,刘景录,孙一康.免疫遗传算法对精轧机组负荷分配的优化[J].北京科技大学学报,2002,24(3):339-341.