Abstract
In the feed sector, 95% of the input costs arise from the supply of raw materials used in feed production. The selling price is determined by competition in free market conditions. Due to the use of similar technologies and the very small share of production costs in total costs, it is unlikely that a competitive advantage will be gained through innovations in production. Between 30% and 50% of grain products are used in feed ration analysis. Cereals can only be harvested at a certain time of the year. Due to this limited time frame, feed production enterprises have to balance their financial burdens with their operational needs while making their annual stocks. The study was carried out to cover all the relevant businesses of the company, which has feed factories in four regions of Turkey. Based on the season data of the year 2020-2021, the grain purchase planning for the year 2021-2022 was tried to be optimized with non-linear programming. While creating the mathematical model, grain prices, interest rates, production needs according to production planning, sales according to sales forecasts, factory stocking capacities, licensed warehouse rental, transportation, handling and transshipment costs were taken into account.
With this unique paper, in the cattle feed production sector, storage, transportation and handling costs will be minimized. Cost advantage will be provided with optimum purchase planning in the season. According to the grain pricing forecast and market data for the 2021-2022 season, model can provide a cost advantage of 0.7%. Model will also provide insight to the managers for additional storage space investments.
Publisher
International Journal of Optimization and Control: Theories and Applications
Subject
Applied Mathematics,Control and Optimization
Reference20 articles.
1. Tay Bayramoglu, Y. D. D. A. & Koç Yurtkur, Y. D. D. A. (2016). Türkiye’de G?da ve Tar?msal Ürün Fiyatlar?n? Uluslararas? Belirleyicileri. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 15 (2) , 63-73.
2. Soysal, M., Bloemhof-Ruwaard, J., Meuwissen, M., & Van der Vorst, J. (2012). A Review on Quantitative Models for Sustainable Food Logistics Management. International Journal of Food System Dynamics. 3. 136-155.
3. Ge, H., Gray, R. & Nolan, J. (2015). Agricultural supply chain optimization and complexity: A comparison of analytic vs simulated solutions and policies. International Journal of Production Economics, 159(C), 208-220.
4. Hosseini, S.M., Motlagh, M.R.G., Samani, F. & Abbasi S. (2019). Strategic optimization of wheat supply chain network under uncertainty: a real case study. Springer Berlin Heidelberg.
5. Mirzapour A., Malekly, H. & Aryanezhad, M.B. (2011). A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty. International Journal of Production Economics. 134. 28-42.