BELİRSİZLİK ALTINDA ÜRETİM PLANLAMADA NİCEL YÖNTEMLERİN KULLANIMI ÜZERİNE BİR DERLEME ÇALIŞMASI

Öz

Bir üretim sürecinde planlama yapmak her dönem için zor olsa da günümüzde belirsizlik unsurlarının artması ile daha dikkatli çalışılması gereken bir konu haline gelmiştir. Bu araştırma, üretim planlamasında belirsizlikleri ele alan ve nicel yöntemler kullanarak belirsizliklerin bulunduğu üretim sürecini optimize eden çalışmaları inceleyen bir derleme çalışması olarak oluşturulmuştur. Dönem olarak 2010-2017 yılları arasında yayımlanan 26 çalışma incelenmiştir. Araştırmada Web of Science veri tabanında taranan öncü dergilerde yayınlanan çalışmalar baz alınmıştır. Çalışmalar; üretim planlamada ele alınan konu ve alt konular, belirsizlik yaratan unsurlar ve belirsizliklerin çözümü için kullanılan nicel yöntemler dikkate alınarak tasnif edilmiştir. Bu çalışma konu ile ilgili çalışan araştırmacılara kaynak oluşturması açısından önemlidir.

Anahtar Kelimeler

• Üretim operasyonları
• belirsizlik altında üretim planlaması
• nicel yöntemler.

Öz

Planning in the production process is a hard problem all the while. Nowadays, because of the increase of uncertainty elements, it has become a subject that needs to be studied more carefully. This study is created as a review study that deals with uncertainties in production process and optimize the process in which under uncertainties with quantitative methods. It examines 26 papers that was published between 2010-2017. It concerned the papers which is in lead journals in Web of Science. The papers has classified regards to subject and sub-topics about production planning, the elements that create uncertainty and the quantitative methods are used for the solution. This study is important in terms of creating a resource for researchers working on the subject.

Anahtar Kelimeler

• Production operations
• production planning under uncertainty
• quantitative methods

Kaynakça

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3. Avraamidou, S., ve Pistikopoulos, E. (2017). A Multiparametric Mixed-integer Bi-level Optimization Strategy for Supply Chain Planning Under Demand Uncertainty. IFAC PapersOnLine, 10178-10183.
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23. Rahmani, D., Ramezanian, R., Fattahi, P., ve Heydari, M. (2013). A robust optimization model for multi-product two-stage capacitated production planning under uncertainty. Applied Mathematical Modelling, 8957–8971.
24. Silva, A. F., ve Marins, F. (2014). A Fuzzy Goal Programming model for solving aggregate production-planning problems under uncertainty: A case study in a Brazilian sugar mill. Energy Economics, 196-204.
25. W.White, S. (2013). An experimentallyconfirmedresourceplanningmodelofservicesunder. Int. J.ProductionEconomics, 484-484.
26. Zeng, X., Zhu, Y., Chen, C., Tong, Y., Li, Y., Huang, G., . . . Wang, X. (2017). A production-emission nexus based stochastic-fuzzy model for identification of urban industry-environment policy under uncertainty. Journal of Cleaner Production, 61-82.
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