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題 名 | 模糊測度應用於多屬性決策時之資訊需求量簡化研究=Reducing the Amount of Information Necessary to Compute Fuzzy Measures Used in Multiattribute Decision Making |
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作 者 | 陳亭羽; 曾國雄; | 書刊名 | 管理學報 |
卷 期 | 17:3 2000.09[民89.09] |
頁 次 | 頁483-514 |
分類號 | 494.542 |
關鍵詞 | 多屬性決策; 模糊測度; 充足資訊; 部份資訊; 抽樣設計; Multiple attribute decision making; Fuzzy measure; Sufficient information; Partial information; Sampling design; |
語 文 | 中文(Chinese) |
中文摘要 | 在多屬性決策分析過程中,以一般模糊測度作為衡量多屬性重要程度之基礎,將可因自由度之增加,使研究者能更真確地描述人類主觀評估過程。然而,因為進行一般模糊測度之求算必須調查所有屬性子集合之資料,在資料蒐集方面相當困難。故本研究擬由實務可行性著手,簡化資料需求量,並發展屬性子集合抽樣與資料收集程序。本研究首先提出可涵蓋所有屬性子集合之充足資訊,其可減少一半之資料需求量。續在充足資訊之架構下,提出部份資訊之抽樣程序,以最少之抽樣數捕捉絕大部份之資訊。經由完全資訊、充足資訊、與部份資訊之比較得知,部份資訊能大幅度降低資料需求量,且在實務應用上有效可行。最後,本研究在部份資訊之抽樣設計下,提供實際應用之問卷調查施行程序,並佐以實例說明。 |
英文摘要 | For multiple attribute decision making analysis, general fuzzy measures that only fulfill the boundary conditions and monotonicity can be used to express the grades of subjective importance of attributes, and the human subjective evaluation process can be accurately approximated because of full degrees of freedom. However, it is difficult to collect complete information regarding all attribute subsets in actual applications for fuzzy measure identification. Thus, this study aims at reducing the information demand of general fuzzy measures. We proposed sufficient information to cover all importance information of attribute subsets. Sufficient information can reduce the information demand by at least one half. Based on the framework of sufficient information, a sampling procedure under partial information was further proposed, in the hope that most information could be captured with the least number of samples. The comparisons among complete, sufficient, and partial information indicate that partial information works effectively in practice and significantly reduces information demand. Finally, we presented an implementation procedure for questionnaire investigation under the sampling design of partial information, and gave an example with illustrations. |
本系統中英文摘要資訊取自各篇刊載內容。