Lagrangian ANN for convex programming with linear constraints
Gong, DJ; Gen, M; Yamazaki, G; Xu, WX
刊名COMPUTERS & INDUSTRIAL ENGINEERING
1997
卷号32期号:2页码:15,429-443
ISSN号0360-8352
英文摘要Convex programming with linear constraints represents a large class of optimization problems which have wide applications, such as linear programming, quadratic programming and some network flow programming problems. In this paper we discuss the artificial neural network approach based on the Lagrangian multiplier method (Lagrangian ANN) to it. The emphases of the paper are on analysing the defect of premature of the conventional Lagrangian ANN and giving a new modification to it in order to overcome its premature defect. We prove that this modified Lagrangian ANN can always give the optimal solution. Numerical simulations demonstrate the effectiveness of the proposed modification. (C) 1997 Elsevier Science Ltd.
学科主题Computer Science, Interdisciplinary Applications ; Engineering, Industrial
语种英语
公开日期2012-11-12
内容类型期刊论文
源URL[http://ir.casipm.ac.cn/handle/190111/5431]  
专题科技战略咨询研究院_中国科学院科技政策与管理科学研究所(1985年6月-2015年12月)
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GB/T 7714
Gong, DJ,Gen, M,Yamazaki, G,et al. Lagrangian ANN for convex programming with linear constraints[J]. COMPUTERS & INDUSTRIAL ENGINEERING,1997,32(2):15,429-443.
APA Gong, DJ,Gen, M,Yamazaki, G,&Xu, WX.(1997).Lagrangian ANN for convex programming with linear constraints.COMPUTERS & INDUSTRIAL ENGINEERING,32(2),15,429-443.
MLA Gong, DJ,et al."Lagrangian ANN for convex programming with linear constraints".COMPUTERS & INDUSTRIAL ENGINEERING 32.2(1997):15,429-443.
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