An Optimization Approach for a Fresh Food Supply Chain: An Application for the Orange Supply Chain Design in Turkey

Year 2021, Volume: 9 Issue: 4, 1563 - 1569, 31.07.2021

Gürkan Güven Güner Durdu Hakan Utku

https://doi.org/10.29130/dubited.790485

Cited By: 2

Abstract

The optimization of supply chain problems in various industry areas is crucial in terms of controlling the quality of the products and costs during the supply chain processes. Protecting and controlling the quality of the product in the food supply chain processes while minimizing the cost is a difficult and critical problem in the food industry. In this study, an application of a model that integrates the quality of the food in decision-making on distribution and production in a food supply chain is implemented using real-life data in Turkey. The degradation of quality of products in storage or transportation is usually based on the storage temperature, storage time, and other constants such as activation energy. Therefore, prediction for the quality of food products is a complex task because of the dynamics of storage conditions and various product characteristics. A methodological approach is proposed to model the degradation of food quality in this study. The rate of quality degradation of food products is evaluated by the proposed approach. A mixed-integer programming model is developed for the optimization of distribution and production planning. To solve the problem, GAMS (General Algebraic Modeling System) CPLEX solver is used as an optimization tool. The results of the case study shows that the suggested model in this study is implementable to the problem with acceptable solution time. In addition, the suggested model is adaptable for different types of food supply chains. This study aims to develop a methodological approach that can be used as a guide for decision-makers.

Keywords

Food Supply Chain, Optimization, Mixed-Integer Linear Programming, Food Industry

Bir Taze Gıda Tedarik Zinciri için Bir Optimizasyon Yaklaşımı: Türkiye’de Portakal Tedarik Zinciri Tasarımı için Bir Uygulama

Abstract

Çeşitli endüstri alanlarında tedarik zinciri problemlerinin optimizasyonu, tedarik zinciri işlemleri süresince ürünlerin kalitesini ve maliyetleri kontrol etmek açısından önemlidir. Gıda tedarik zinciri işlemlerinde maliyeti en küçüklerken ürünün kalitesini korumak ve kontrol etmek, gıda endüstrisinde zor ve kritik bir problemdir. Bu çalışmada, bir ürünün kalitesini bir gıda tedarik zincirinde dağıtım ve üretim üzerine karar vermede entegre eden bir modelin Türkiye’deki gerçek hayat verilerinin kullanılmasıyla bir uygulaması yapılmıştır. Depolama ve taşımada ürünlerin kalitesinin bozulması genellikle depolama sıcaklığına, depolama zamanına ve aktivasyon enerjisi gibi başka sabitlere bağlıdır. Bu sebeple, depolama kondisyonlarının dinamiklerinden ve çeşitli ürün karakteristiklerinden dolayı, gıda ürünlerinin kalitesinin tahmini kompleks bir iştir. Bu çalışmada gıda kalitesinin bozulmasını modellemek için metodolojik bir yaklaşım önerilmiştir. Gıda ürünlerinin kalite bozulmasının oranı önerilen yaklaşım ile hesaplanmıştır. Dağıtım ve üretim planlamanın optimizasyonu için bir karma-tam sayılı programlama modeli geliştirilmiştir. Problemi çözmek için GAMS (General Algebraic Modeling System) CPLEX çözücüsü bir optimizasyon aracı olarak kullanılmıştır. Durum çalışmasının sonuçları bu çalışmada önerilen modelin kabul edilebilir bir çözüm zamanı ile probleme uygulanabilir olduğunu göstermiştir. Ayrıca, önerilen model farklı tipteki tedarik zincirlerine uyarlanabilirdir. Bu çalışma, karar vericiler için bir rehber olarak kullanılabilecek bir metodolojik yaklaşımı geliştirmeyi hedeflemektedir.

Keywords

Gıda Tedarik Zinciri, Optimizasyon, Karma-Tam Sayılı Doğrusal Programlama, Gıda Endüstrisi

References

• [1] D.P. Van Donk, R. Akkerman and T. VanderVaart, “Opportunities and realities of supply chain integration: The case of food manufacturers,” British Food Journal, vol. 110, pp. 218–235, 2018.
• [2] D. Smith and L. Sparks, “Temperature controlled supply chains,” in Food Supply Chain Management, M.A. Bourlakis and P.W.H. Weightman, Eds., Oxford, U.K.: Blackwell Publishing, 2004, pp. 179–198.
• [3] R. Manzini, R. Accorsi, Z. Ayyad, A. Bendini, M. Bortolini, G. Gamberi, E. Valli and T.G. Toschi, “Sustainability and quality in the food supply chain. A case study of shipment of edible oils,” British Food Journal, vol. 116, pp. 2069-2090, 2014.
• [4] J. Trienekens and P. Zuurbier, “Quality and safety standards in the food industry, developments and challenges,” International Journal of Production Economics, vol. 113, pp. 107–122, 2008.
• [5] M. Lütke Entrup, H.O. Günther, P. VanBeek, M. Grunow and T. Seiler, “Mixed-integer linear programming approaches to shelf-life-integrated planning and scheduling in yoghurt production,” International Journal of Production Research, vol. 43, pp. 5071–5100, 2005.
• [6] F. Sgarbossa and I. Russo, “A proactive model in sustainable food supply chain: Insight from a case study,” International Journal of Production Economics, vol. 183, pp. 596–606, 2017.
• [7] D. Zilberman, L. Lu and T. Reardon, “Innovation-induced food supply chain design,” Food Policy, vol. 83, pp. 289–297, 2019.
• [8] H. Allaoui, Y. Guo, A. Choudhary. and J. Bloemhof, “Sustainable agro-food supply chain design using two-stage hybrid multi-objective decision-making approach,” Computers and Operations Research, vol. 89, pp. 369–384, 2018.
• [9] A. Rong, R. Akkerman and M. Grunow, “An optimization approach for managing fresh food quality throughout the supply chain,” International Journal of Production Economics, vol. 131, pp. 421–429, 2011.
• [10] M.M. Aung and Y.S. Chang, “Traceability in a food supply chain: safety and quality perspectives,” Food Control, vol. 39, pp. 172-184, 2014.
• [11] R. Manzini and R. Accorsi, “The new conceptual framework for food supply chain assessment,” Journal of Food Engineering, vol. 115, pp. 251-263, 2013.
• [12] M. Yu and A. Nagurney, “Competitive food supply chain networks with application to fresh produce,” European Journal of Operational Research, vol. 224, pp. 273-282, 2013.
• [13] M.M. Aung and Y.S. Chang, “Temperature management for the quality assurance of a perishable food supply chain,” Food Control, vol. 40, pp. 198-207, 2014.
• [14] A. Diabat, K. Govindan and V.V. Panicker, “Supply chain risk management and its mitigation in a food industry,” International Journal of Production Research, vol. 50, pp. 3039-3050, 2012.
• [15] Republic of Turkey Ministry of Agriculture and Forestry, Agricultural Economic and Policy Development Institute. (2020, January). Tarım Ürünleri Piyasaları [Online]. Available: https://arastirma.tarimorman.gov.tr/tepge/Belgeler/PDF%20Tar%C4%B1m%20%C3%9Cr%C3%BCnleri%20Piyasalar%C4%B1/2020Ocak%20Tar%C4%B1m%20%C3%9Cr%C3%BCnleri%20Raporu/Portakal%20Tar%C4%B1m%20%C3%9Cr%C3%BCnleri%20Piyasa%20Raporu%202020%20ocak.pdf
• [16] Merkezi Dağıtım Sistemi dataset: Concatenated, 2014 to 2019, TÜİK (Turkish Statistical Institute), Aug. 2020. [Online]. Available: https://biruni.tuik.gov.tr/medas/?kn=104&locale=tr
• [17] R. H. Shumway and D. S. Stoffer, “Time series regression and ARIMA models,” in Time Series Analysis and Its Applications, New York, U. S.: Springer, 2000, pp. 89-212.
• [18] P. S. P. Cowpertwait and A. V. Metcalfe, “Non-seasonal ARIMA models,” in Introductory Time Series with R, New York, U. S.: Springer, 2009, pp. 134-141.
• [19] Republic of Turkey Ministry of Agriculture and Forestry, Agricultural Economic and Policy Development Institute. (2019, July). Tarım Ürünleri Piyasaları [Online]. Available: https://arastirma.tarimorman.gov.tr/tepge/Belgeler/PDF%20Tar%C4%B1m%20%C3%9Cr%C3%BCnleri%20Piyasalar%C4%B1/2019Temmuz%20Tar%C4%B1m%20%C3%9Cr%C3%BCnleri%20Raporu/2019-Temmuz%20Portakal.pdf
• [20] Republic of Turkey Ministry of Agriculture and Forestry, Agricultural Economic and Policy Development Institute. (2020, July). Tarım Ürünleri Piyasaları [Online]. Available: https://arastirma.tarimorman.gov.tr/tepge/Belgeler/PDF%20Tar%C4%B1m%20%C3%9Cr%C3%BCnleri%20Piyasalar%C4%B1/2020Temmuz%20Tar%C4%B1m%20%C3%9Cr%C3%BCnleri%20Raporu/Portakal,%20Temmuz2020,%20Tar%C4%B1m%20%C3%9Cr%C3%BCnleri%20Piyasa%20Raporu.pdf
• [21] Adrese Dayalı Nüfus Kayıt Sistemi dataset: Concatenated, 2014 to 2019, TÜİK (Turkish Statistical Institute), Aug. 2020. [Online]. Available: http://www.tuik.gov.tr/PreTablo.do?alt_id=1059
• [22] S.K. Wang, Handbook of Air Conditioning and Refrigeration, 2nd ed. New York, NY, USA: McGraw-Hill, 2001.
• [23] Distance Calculator dataset, Republic of Turkey General Directorate of Highways, Aug. 2020. [Online]. Available: https://www.kgm.gov.tr/Sayfalar/KGM/SiteTr/Uzakliklar/illerArasiMesafe.aspx