整合類神經網路與多屬性決策分析法於綠色供應商評選之研究

Integration of Neural Network and MADA Method for Green Supplier Selection

王奕琪(Yi-Chi Wang)

指導教授 ： 田方治 ； 郭人介

國立臺北科技大學/管理學院/工業工程與管理研究所/碩士(2009年)

摘要

近年來，隨著環保意識抬頭與企業追求永續發展，綠色議題在供應鏈管理中越來越顯得重要，此概念稱之為綠色供應鏈管理 (Green Supply Chain Management)。本研究將考量傳統供應鏈選擇評估準則與環保相關議題，發展出一套綠色供應商評選架構。
本研究將類神經網路(Artificial Neural Network)與兩個多屬性決策分析(Multi Attribute Decision Analysis)方法：資料包絡分析法(Data Envelopment Analysis) 與 分析網路程序法 (Analytic Network Process )進行整合，提出ANN-MADA供應商評選方法。此方法能克服傳統資料包絡分析法資料正確性與決策單位(Decision Making Units)數量的限制。本研究將ANN-MADA與另外兩個整合式方法：ANN-DEA與ANP-DEA進行比較，發現ANN-MADA在綠色供應商評選問題中有較好的鑑別力與雜訊處理能力。

關鍵字

綠色供應商選擇 ； 資料包絡分析法 ； 分析網路程序法 ； 類神經網路

並列摘要

In recent years, with the raising of awareness in environmental protection and enterprise sustainable development, green issue has become more and more critical in supply chain management. This concept is named Green Supply Chain Management (GSCM). This research intends to develop a green supplier selection model which considers both practicability in traditional supplier selection criteria and environmental regulations.
This research integrates two Multi Attribute Decision Analysis (MADA) methods: Data Envelopment Analysis (DEA) and Analytic Network Process (ANP) with Artificial Neural Network (ANN) which become ANN-MADA hybrid method. This approach can overcome traditional DEA drawbacks: limitations of data accuracy and DMUs amounts constraint. In case study, ANN-MADA hybrid method is compared with other hybrid methods ANN-DEA and ANP-DEA, and it is discovered that ANN-MADA has better power of discrimination and noise-insensitivity in evaluating green suppliers’ performances.

並列關鍵字

Green Supplier Selection ； Data Envelopment Analysis ； Analytic Network Process ； Artificial Neural Network

參考文獻

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