全球智库信息集成服务系统(G2TT): Interactive Multiple Objective Programming Using Tchebycheff Programs and Artificial Neural Networks.

G2TT

来源类型	Monograph (IIASA Working Paper)
规范类型	论文
	Interactive Multiple Objective Programming Using Tchebycheff Programs and Artificial Neural Networks.
	Sun M; Stam A; Steuer RE
发表日期	1995
出版者	IIASA, Laxenburg, Austria: WP-95-058
出版年	1995
语种	英语
摘要	A new interactive multiple objective programming procedure is developed that combines the strengths of the Interactive Weighted Tchebycheff Procedure (Steuer and Choo 1983) and the Interactive FFANN Procedure (Sun, Stam and Steuer 1993). In this new procedure, nondominated trial solutions are generated by solving Augmented Weighted Tchebycheff Programs (Steuer 1986), based on which the decision maker articulates his/her preference information by assigning "values" to these solutions or by making pairwise comparisons. The elicited preference information is used to train a feed-forward artificial neural network, which in turn is used to screen new trial solutions for presentation to decision maker in the next iteration. Computational results are reported, comparing the current procedure with the Interactive Weighted Tchebycheff Procedure and the Interactive FFANN Procedure. The results show that this new procedure yields good quality solutions.
主题	Methodology of Decision Analysis (MDA)
URL	http://pure.iiasa.ac.at/id/eprint/4535/
来源智库	International Institute for Applied Systems Analysis (Austria)
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/124412
推荐引用方式 GB/T 7714	Sun M,Stam A,Steuer RE. Interactive Multiple Objective Programming Using Tchebycheff Programs and Artificial Neural Networks.. 1995.

条目包含的文件
文件名称/大小	资源类型	版本类型	开放类型	使用许可
WP-95-058.pdf（883KB）	智库出版物		限制开放	CC BY-NC-SA	浏览