本研究提出一套整合正、逆向物流之供應鏈設計模式，考量環境永續議題與市場供需資訊之不確定性，決定逆物系統之建置，包括流潛在廠區位置(location)、運輸流量(flow)、產能(capacity)與技術(technology)投資設計，並過穩健多目標最佳化方法(Robust Multi-objective Programming Model; RMOP)，權衡整體供應鏈設計之總成本(total cost)與二氧化碳排放約當量(CO2e)。數值分析結果指出，逆物流系統建置會依據不同的原物料取得成本與市場不確定性而呈現不同的經濟效益；並透過柏拉圖最適解集合(Pareto-optimal Set)，分析成本與二氧化碳排放之間的影響，並依據不同的碳排放上限(Cap)給予企業兼具成本與環境效益的供應鏈設計結果。除此之外，本研究亦驗證穩健最佳化模型(robust model)與確定型模型(deterministic model)，於不同市場不確定下，供應鏈設計之穩健性績效。最後，以矽晶太陽能產業為案例，說明正逆物流整合型永續供應鏈設計於實務上之重要性與可行性。 This paper studies an integrated forward and reverse supply chain network design problem with sustainable concerns under the uncertain environment. We are interested in the logistics flows, capacity expansion and technology investments of existing and potential facilities, and consider the uncertainty occurred in raw material supply, customer demand and return quantity. A robust multi-objective programming model (RMOP), that captures the trade-off between the total cost and the carbon dioxide (CO2) emission, is developed from the economic and environmental perspective, respectively.In the numerical evaluation and results, we analyzed the relationship between the total cost and carbon emission in integrated supply chain network and robustness of the proposed RMOP model by the generated Pareto-optimal set. Finally, a case study of crystalline solar energy industry is applied to illustrate the importance of developing an integrated forward and reverse supply chain network design model in practice.
