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    政大機構典藏 > 商學院 > 資訊管理學系 > 學位論文 >  Item 140.119/119882


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    题名: 考慮供應中斷風險下最適訂貨與定價模型 —利潤與數量彈性之目標規劃
    Optimization of Ordering and Pricing Model under Risk of Interruption-Goal Programming of Profit and Resilient Supply Chain
    作者: 黃雅詩
    Huang, Ya-Shih
    贡献者: 林我聰
    Lin, Woo-Tsong
    黃雅詩
    Huang, Ya-Shih
    关键词: 供應鏈中斷
    彈性供應鏈
    優先型目標規劃
    Supply chain disruption
    Resilient supply chain
    Preemptive goal programming
    日期: 2018
    上传时间: 2018-09-03 15:48:04 (UTC+8)
    摘要: 近年來，供應鏈中斷的事件頻傳，不論是地震、水災等自然災害、大規模傳染病、恐怖攻擊......等，也因為供應鏈的全球化，導致供應商中斷的影響範圍比以往更擴大。由於供應鏈的脆弱和不確定性，以及中斷後續所帶來的影響和損失，促使企業更看重中斷事件前，供應鏈該如何管理及反應，學者們也對中斷供應鏈管理比以往有更多的研究，若能在中斷之前有所防範，不只是被動的等待中斷發生後才有補救的行為，更可以成為企業的核心競爭力。
    為了因應供應鏈中斷之後的各種影響，企業在購買原料、製造產品的過程中，提高原料或是產品在數量上的彈性也將納入決策的一環，但是相對的，數量彈性的提高也會使得企業總成本提升，因此企業必須考量企業利潤的最大化，同時想辦法滿足顧客需求，以提高顧客滿意程度。
    本研究希望建構一個決策模型，透過企業在供應中斷之前，考量中斷風險因子的行為，應用在替顧客定價、決定購買原料數量的決策之中，以期達成利潤最大化與彈性最大化之多目標供應鏈模式，而決策者在面對此兩項目標時，又可依據心中欲達成目標之先後順序，分為下列兩種決策情境：(1)利潤目標優先達成、(2)彈性目標優先達成。此兩項目標的權重難以量化，多是靠經驗判定，因此本研究將使用目標規劃之中的優先型目標規劃，以優先順序分別呈現兩種情境，以供決策者參考。
    In recent years, there are frequent incidents of disruptions in the supply chain, whether natural disasters such as earthquakes or floods, large-scale infectious diseases, terrorist attacks, etc. Because of the globalization of the supply chain, disruptions result in a wider range and expanded even more in the past. Due to the fragility and uncertainty of the supply chainm in addition to the impact and losses caused by the interruption, enterprises are more concerned about how supply chain manage and react before the disruption. Scholars also have more research in interruptions of supply chain management than ever. If enterprise can prevent before the interruption happen, not just waiting passively for the remedy after the interruption, it can become the enterprise`s core competitiveness.
    In order to respond to the various impacts of the supply chain disruption, how enterprise increase the elasticity of the raw materials or products in terms of quantity will also be included in the decision-making process that purchasing raw materials and manufacturing products will. But in the same time, the total cost will increase, so enterprises must consider the maximization of corporate profits, while trying to meet customer needs that is the way to improve customer satisfaction.
    This study hopes to construct a decision model that considers the interruptinn risk factors and applies them to the pricing and the how much to purchase raw materials. When decision-makers in the face of these two goals, usually based on their experiences and not easy to weight them. Therefore, this study will use the Preemptive Goal Programming to present two scenarios : (1) the profit goal is achieved first, and (2) the elastic target is reached first in order of priority for decision-makers` reference.
    參考文獻: Gandhi, K., & Jha, P. C. (2014). Fuzzy bi-objective optimization model for multi-echelon distribution network. RATIO MATHEMATICA, 26, 39-64.
    Hisjam, M., Guritno, A. D., Supriyatno, N., & Tandjung, S. D. (2015). A Sustainable Partnership Model among Supply Chain Players in Wooden Furniture Industry Using Goal Programming. Agriculture and Agricultural Science Procedia, 3, 154-158.
    Ivanov, D., Pavlov, A., Dolgui, A., Pavlov, D., & Sokolov, B. (2016). Disruption-driven supply chain (re)-planning and performance impact assessment with consideration of pro-active and recovery policies. Transportation Research, 7-24.
    Kristianto, Y., Gunasekaran, A., Helo, P., & Hao, Y. (2014). A model of resilient supply chain network design: A two-stage programming with fuzzy shortest path. Expert Systems with Applications, 41, 39-49.
    Li, X., & Barnes, I. (2008). Proactive supply risk management methods for building a robust supply selection process when sourcing from emerging markets. Strategic Outsourcing: An International Journal, 1(3), 252-267.
    Raj, R., Wang, J. W., Nayak, A., Tiwari, M. K., Han, B., Liu, C. L., & Zhang, W. J. (2015). Measuring the Resilience of Supply Chain Systems Using a Survival Model. IEEE SYSTEMS JOURNAL, 9(2), 377-381.
    Ruiz-Torres, A. J., & Mahmoodi, F. (2007). The optimal number of suppliers considering the costs of individual supplier failures. Science Direct, 104-115.
    Sawik, T. (2014). Optimization of cost and service level in the presence of supply chain disruption risks: Single vs. multiple sourcing. Computers & Operations Research, 11-20.
    Schmitt, A. J. (2011). Strategies for customer service level protection under multi-echelon supply chain disruption risk. Transportation Research, 1266-1283.
    Scholten, K., & Schilder, S. (2015). The role of collaboration in supply chain resilience. Supply Chain Management: An International Journal of Production Research, 20(4), 471-484.
    Torabi, S. A., Baghersad, M., & Mansouri, S. A. (2015). Resilient supplier selection and order allocation under operational and disruption risks. Transportation Research, 22-48.
    Tzeng, G.-H., Tang, T.-I., Hung, Y.-M., & Chang, M.-L. (2006). Multiple-objective planning for a production and distribution model of the supply chain: Case of a bicycle manufacturer. Journal of Scientific & Industrial Research, 65, 309-320.
    Wu, T., Blackhurst, J., & O’Grady, P. (2007). Methodology for supply chain disruption analysis. International Journal of Production Research, 45(7), 1665–1682.
    Xiao, T., & Qi, X. (2008). Price competition, cost and demand disruptions and coordination of a supply chain with one manufacturer and two competing retailers. Omega, 741-753.
    描述: 碩士
    國立政治大學
    資訊管理學系
    105356033
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0105356033
    数据类型: thesis
    DOI: 10.6814/THE.NCCU.MIS.022.2018.A05
    显示于类别:[資訊管理學系] 學位論文

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