بهینه‌سازی زنجیره تامین لبنی در استان کردستان با در نظر گرفتن محصولات ثانویه

فصلنامه علمی -پژوهشی تحقیقات اقتصاد کشاورزی

مقاله 14، دوره 12، شماره 47، آبان 1399، صفحه 25-48   

نوع مقاله: مقاله پژوهشی

نویسندگان

سیده روزیتا ابراهیمی¹؛ فرید خوش الحان^{* 2}؛ حامد قادرزاده³

¹دانشکده مهندسی صنایع، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران و ایران

²دپارتمان مهندسی صنایع، دانشکده مهندسی صنایع، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران، ایران

³عضو هیئت علمی گروه اقتصاد کشاورزی دانشگاه کردستان

تاریخ دریافت: 25 مهر 1396،  تاریخ بازنگری: 31 شهریور 1397،  تاریخ پذیرش: 12 آذر 1397 

چکیده

صنعت لبنی جایگاه ویژه‌ای در صنایع غذایی جهانی دارد. موضوع محصولات ثانویه در کاهش ضایعات، ایجاد ارزش افزوده‌ی بالا و کاهش اثرات زیست‌محیطی متناظر به عنوان بخشی از مولفه‌های زنجیره تامین لبنی قابل طرح است. به دلیل ارزش غذایی و هم‌چنین شامل شدن هزینه‌های تولیدی این محصولات انجام تمهیداتی به منظور کاهش ضایعات و تامین غذای بیشتر، اقتصادی به نظر می‌رسد. در بین محصولات ثانویه در فرایند فراوری محصولات لبنی، آب پنیر به عنوان مهم‌ترین و مغذی‌ترین ماده‌ی ثانویه شناخته شده است. مقاله‌ی حاضر تلاش می‌نماید، با توسعه‌ی مدل‌های موجود در زنجیره تامین لبنی و افزودن متغیر تصمیم محصولات ثانویه به آن، گامی در راستای تحقق این اهداف بردارد. با تحلیل و آنالیز مدل جدید با بهره‌گیری از داده‌های صنعت لبنیات استان کردستان سودآوری این زنجیره پس از دخیل کردن تاثیر محصول ثانویه‌ی آب پنیر، به طور معنی‌داری افزایش می‌یابد.

کلیدواژه‌ها

زنجیره تامین لبنی؛ بهینه‌سازی؛ محصولات ثانویه؛ ضایعات مواد غذایی - استان کردستان ایران

عنوان مقاله [English]

Optimization of Kurdistan – Iran dairy supply chain by considering byproducts

نویسندگان [English]

S. R. Ebrahimi¹؛ F. Khoshalhan²؛ H. Ghaderzadeh³

¹Industrial Engineering Department of K N Toosi University of Technology, Iran

²Faculty member of Industrial Engineering Department of K N Toosi University of Technology.

³Faculty member of Agricultural Economics Department of the University of Kurdistan.

چکیده [English]

The dairy industry has a special place in the global food industry. The theme of byproducts is to reduce waste, create high added value and reduce the corresponding environmental effects as part of the components of the dairy supply chain. Because of the nutritional value and also the cost of producing these products, measures to reduce waste and provide more food are economical. Among the byproducts in the process of processing dairy products, whey is considered to be the most important and nutritious ingredient. The present paper tries to develop a model in the supply chain of dairy products and add the variable of the decision of byproducts to it, a step towards achieving these goals. By analyzing and analyzing the new model using data from the dairy industry in Kurdistan province, the profitability of this chain increases significantly after affecting the effect of whey production.

کلیدواژه‌ها [English]

Dairy Supply Chain, Optimization, Byproducts, Food waste, Kurdistan Iran province

مراجع

- Adonyi, R., Shopova, E. & Vaklieva-Bancheva, N. (2009). Optimal schedule of a dairy manufactory. Chemical and Biochemical Engineering Quarterly, 23:231–237.

- Ahumada, O., & J. R. Villalobos. (2009). Application of planning models in the agro-food supply chain: A review. European Journal of Operational Research, 196: 1–20.

- Banaszewska, A. & Cruijssen, F. (2013). A comprehensive dairy valorization model. Journal of Dairy Science, 96:761–779.

- Banaszewska, A., Cruijssen, F., Claassen, G. D. H. & van der Vorst, J. G. A. J. (2014). Effect and key factors of byproducts valorization: The case of dairy industry. Journal of Dairy Science, 97 :1893–1908.

- Bello, N.M., Stevenson, J.S. & Tempelman, R.J. (2012). Invited review: Milk production and reproductive performance: Modern interdisciplinary insights into an enduring axiom. . Journal of Dairy Science, 95: 5461 – 5475.

- Benseman, B. R. (1986). Production planning in the New Zealand dairy industry. Journal of the Operational Research Society, 37: 747–754.

- Bourlakis, M., Maglaras, G., Aktas, E., Gallear, D. & Fotopoulos, Ch. (2013). Firm size and sustainable performance in food supply chains: Insights from Greek SMEs. International Journal of Production Economics.
-Burke, J. A. (2006). Two mathematical programming models of cheese manufacture. Journal of Dairy Science, 89:799–809.

- Birge, J. & Louveaux, F. (1997). Introduction to Stochastic Programming. Springer Seriesin Operations Research. Springer-Verlag, New York.

- Craig, K.L., Norback, J.P. & Johnson, M.E. (1989). A Linear Programming Model Integrating Resource Allocation and Product Acceptability for Processed Cheese Products.

- Doganis, P., & H. Sarimveis. (2007). Optimal scheduling in a yogurt production line based on mixed integer linear programming. Journal of Food Engineering, 80: 445–453.

- Doole, G. J., Alvaro, A. J., & Adler, A. A. (2012). A mathematical model of a New Zealand dairy farm: The Integrated Dairy Enterprise Analysis (IDEA) framework. Working Paper 1201. Waikato University Department of Economics, Hamilton, New Zealand.

- Duan, Q. & Liao T.W. (2013). A new age-based replenishment policy for supply chain inventory optimization of highly perishable products. International Journal of Production Economics, 145: 658-671.

- Ergüder, T.H., Tezel, U., Güven, E. & Demirer, G.N. (2001). Anaerobic biotransformation and methane generation potential of cheese whey in batch and UASB reactors. Waste Manage. 21 (7), 643-650.

- Geary, U., N. Lopez-Villalobos, D. J., Garrick, & Shalloo, L. (2010). Development and application of a processing model for the Irish dairy industry. Journal of Dairy Science, 93:5091–5100.

- Guan, Z., & A. B. Philpott. (2011). A multistage stochastic programming model for the New Zealand dairy industry. International Journal of Production Economics, 134:289–299.

- Guan, Z. & Philpott, A.B. (2011). A multistage stochastic programming model for the New Zealand dairy industry. International Journal of Production Economics, 134: 289–299.

- Hovelaque,V., Duvaleix-Tréguer,S. & Cordier, J (2009), Effects of constrained supply and price contracts on agricultural cooperatives. European Journal of Operational Research, 199: 769–780.

- Kerrigan, G. L., & Norback, J. P. (1986). Linear programming in the allocation of milk resources for cheese making. Journal of Dairy Science, 69: 1432–1440.

- Koutinas, A., Papapostolou, H., Dimitrellou, D. & Kopsahelis, N. (2009). Whey valorisation: A complete and novel technology development for dairy industry starter culture production. Bioresource Technology Journal, 100, 3734–3739.

- Johnson, H.A., Parvin, L., Garnett, I., DePeters, E. J., Medrano, J. F. & Fadel. J. G. (2007). Valuation of milk composition and genotype in cheddar cheese production using an optimization model of cheese and whey production. Journal of Dairy Science ,90:616–629.

- Lutke-Entrup, M., Gunther, H.O., Van Beek, P., Grunow, M. & Seiler. T. (2005). Mixed-integer linear programming approaches to shelf-life-integrated planning and scheduling in yoghurt production. International Journal of Production Research,43:5071–5100.

- Mellalieu, P. J. & Hall, K. R. (1983). An interactive planning model for the New Zealand dairy industry. Journal of the Operational Research Society, 34:521– 532.

- Papadatos, A., Berger, A. M., Pratt, J. E. & Barbano, D. M. (2002). A nonlinear programming optimization model to maximize net revenue in cheese manufacture. Journal of Dairy Science, 85:2768–2785.

- Perrot, N., De Vries, H. & Lutton, E. (2015). Some remarks on computational approaches towards sustainable complex agri-food systems. Trends in Food Science & Technology: 1-14.

- Pinior, B., Conraths, Franz J. & Petersen, B. Reprintof (2015) .“Decision support for risks managers in the case of deliberate food contamination: The dairy industry as an example”. Omega, 57: 114–122.

- Roupas, P. (2008). Predictive modeling of dairy manufacturing processes. International Dairy Journal, 18:741–753.

- Sadeghi, J., Mousavi, S.M., Akhavan Niaki, S.T. & Sadeghi, S. (2014). Optimizing a bi-objective inventory model of a three-echelon supply chain using a tuned hybrid bat algorithm. Transportation Research, 70: 274 – 292.

- Sethanan, K. & Pitakaso, R. (2016). Differential evolution algorithms for scheduling raw milk transportation. Computers and Electronics in Agriculture, 121: 245–259.

- Strande´n, I. & Lidauer, M. (2001). Parallel Computing Applied to Breeding Value Estimation in Dairy Cattle. Journal of Dairy Science, 84 : 276-285.

- Vaklieva-Bancheva, N., Espuna, A., Shopova, E., Puigjaner, L. & Ivanov, B. (2007). Multi-objective optimization of dairy supply chain. Computer Aided Chemical Engineering, 24:781–786.

- Validi, S., Bhattacharya, A. & Byrne, P.J. (2014). A case analysis of a sustainable food supply chain distribution system—A multi-objective approach. International Journal of Production Economics, 152: 71–87.

- Vellinga, Th.V., Bannink, A., Smits, M.C.J., Dasselaar, A., Van den Pol-Van & Pinxterhuis, I. (2011). Intensive dairy production systems in an urban landscape, the Dutch situation. Livestock Science, 139: 122–134.

- Wouda, F. H. E., P. van Beek, J. G. A. J. van der Vorst, & H. Tacke. (2002). An application of mixed-integer linear programming models on the redesign of the supply network of Nutricia Dairy & DrinksGroup in Hungary. Spectrum, 24: 449–465.

- Yates, C. M. & Rehman, T. (1998). A Linear Programming Formulation of the Markovian Decision Process Approach to Modeling the Dairy Replacement Problem. Agricultural Systems, 2 : 185-201.

- Yu, M. & Nagurney, A. (2013). Competitive food supply chain networks with application to fresh produce. European Journal of Operational Research, 224: 273–282.

- Zarei, M., Fakhrzad, M. B. & Jamali Paghaleh, M. (2011) . Food supply chain leanness using a developed QFD model. Journal of Food Engineering, 102: 25–33.