綠色產品設計與開發逐漸受到重視，產品從設計到出售必需限制產品對環境造成的衝擊，以減少產品對環境的負面影響。本研究提出多目標確定性與單一目標不確定性兩種模型。為了尋找符合環保法規限制的最佳產品設計與供應鏈決策，並考量經濟因素，本研究的多目標確定性模型，利用基因演算法(Genetic Algorithm, GA)搜尋可能的設計選項，使用網路數學模型建立相對應的供應鏈網路，並將此網路模型轉化為前K條最短路徑問題（K-Shortest Paths, KSP），最後使用Yen’s algorithm求解。基於生命週期（Life Cycle Assessment, LCA）評估原料、製造、與運輸過程的碳排放量，配合成本參數，計算不同決策組合的成本和碳排放量，藉此找到滿足碳排放量限制同時最小化成本的最佳解。此外為了考量產品開發過程中LCA對環境衝擊評估的不確定性，本研究提出單一目標不確定性模型，假設碳排放量服從統計機率分配，以基因演算法搜尋產品設計選項，使用網路數學模型建立相對應的供應鏈網路，基於Yen’s algorithm發展演算法最大化不同設計選項與不同供應鏈的決策組合中符合碳排放量限制之機率。

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