全球智库信息集成服务系统(G2TT): Solving multiple objective programming problems using feed-forward artificial neural networks: The interactive FFANN approach.

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来源类型	Article
规范类型	其他
	Solving multiple objective programming problems using feed-forward artificial neural networks: The interactive FFANN approach.
	Sun M; Stam A; Steuer RE
发表日期	1996
出处	Management Science 42 (6): 835-849.
出版年	1996
语种	英语
摘要	In this paper, we propose a new interactive procedure for solving multiple objective programming problems. Based upon feed-forward artificial neural networks (FFANNs), the method is called the Interactive FFANN Procedure. In the procedure. In the procedure, the decision maker articulates preference information over representative samples from the nondominated set either by assigning preference "values" to the sample solutions or by making pairwise comparisons in a fashion similar to that in the Analytic Hierarchy Process. With this information, a FFANN is trained to represent the decision maker's preference structure. Then, using the FFANN, an optimization problem is solved to search for improved solutions. An example is given to illustrate the Interactive FFANN Procedure. Also, the procedure is compared computationally with the Tchebycheff Method (Steuer and Choo 1983). The computational results indicate that the Interactive FFANN Procedure procedures good solutions and is robust with regard to the neural network architecture.
主题	Methodology of Decision Analysis (MDA)
URL	http://pure.iiasa.ac.at/id/eprint/4635/
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/127495
推荐引用方式 GB/T 7714	Sun M,Stam A,Steuer RE. Solving multiple objective programming problems using feed-forward artificial neural networks: The interactive FFANN approach.. 1996.