| 来源类型 | Article
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| 规范类型 | 其他
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| DOI | 10.1016/S0305-0548(99)00108-2
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| Interactive multiple objective programming using Tchebycheff programs and artificial neural networks. |
| Sun M; Stam A; Steuer RE
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| 发表日期 | 2000
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| 出处 | Computers & Operations Research 27 (7-8): 601-620
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| 出版年 | 2000
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| 语种 | 英语
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| 摘要 | A new interactive multiple objective programming procedure is developed that combines the strengths of the interactive weighted Tchebycheff procedure (Steuer and Choo. Mathematical Programming 1983;26(1):326–44.) and the interactive FFANN procedure (Sun, Stam and Steuer. Management Science 1996;42(6):835–49.). In this new procedure, nondominated solutions are generated by solving augmented weighted Tchebycheff programs (Steuer. Multiple criteria optimization: theory, computation and application. New York: Wiley, 1986.). The decision maker indicates preference information by assigning “values” to or by making pairwise comparisons among these solutions. The revealed preference information is then used to train a feed-forward artificial neural network. The trained feed-forward artificial neural network is used to screen new solutions for presentation to the decision maker on the next iteration. The computational experiments, comparing the current procedure with the interactive weighted Tchebycheff procedure and the interactive FFANN procedure, produced encouraging results. |
| 主题 | Institute Scholars (INS)
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| URL | http://pure.iiasa.ac.at/id/eprint/14200/
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| 来源智库 | International Institute for Applied Systems Analysis (Austria)
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| 引用统计 |
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| 资源类型 | 智库出版物
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| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/127869
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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.. 2000.
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