Neural network approach for allocation with capacity
Gong, DJ; Gen, MS; Yamazaki, G; Xu, WX
1996
Source PublicationCOMPUTERS & INDUSTRIAL ENGINEERING
ISSN0360-8352
Volume31Issue:40972Pages:6,849-854
AbstractIn this paper we discuss neural network approach for allocation with capacity constraints problem. This problem can be formulated as zero-one integer programming problem. We transform this zero-one integer programming problem into an equivalent nonlinear programming problem by replacing zero-one constraints with quadratic concave equality constraints. We propose two kinds of neural network structures based on penalty function method and augmented Lagrangian multiplier method, and compare them by theoretical analysis and numerical simulation. We show that penalty function based neural network approach is not good to combinatorial optimization problem because it falls in the dilemma whether terminating at an infeasible solution or sticking at any feasible solution, and augmented Lagrangian multiplier method based neural network can alleviate this suffering in some degree.
KeywordNeural Network Allocation Integer Programming Penalty Function Method Augmented Lagrangian Multiplier Method
Subject AreaComputer Science, Interdisciplinary Applications ; Engineering, Industrial
Indexed BySCI
Language英语
Document Type期刊论文
Identifierhttp://ir.casisd.cn/handle/190111/5427
Collection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)
Recommended Citation
GB/T 7714
Gong, DJ,Gen, MS,Yamazaki, G,et al. Neural network approach for allocation with capacity[J]. COMPUTERS & INDUSTRIAL ENGINEERING,1996,31(40972):6,849-854.
APA Gong, DJ,Gen, MS,Yamazaki, G,&Xu, WX.(1996).Neural network approach for allocation with capacity.COMPUTERS & INDUSTRIAL ENGINEERING,31(40972),6,849-854.
MLA Gong, DJ,et al."Neural network approach for allocation with capacity".COMPUTERS & INDUSTRIAL ENGINEERING 31.40972(1996):6,849-854.
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