PASTÖRİZE LİKİT YUMURTA ÜRETİM PLANI OPTİMİZASYONU

Üretim planlama; hammadde, ürün ve makine kısıtları arasındaki ilişkiler karmaşıklaştığında zor bir optimizasyon problemi haline gelmektedir. Çalışma kapsamında, belirli üretim kısıtları altında likit yumurta üretim planı optimize edilmektedir. Problemin çözümünde, uygulamada karşılaşılan kısıtların göz önüne alındığı “Genelleştirilmiş İndirgenmiş Gradyenler” temelli bir üretim planı modeli geliştirilmiştir. Geliştirilen model kapsamında ortaya çıkan üretim planı, ürün karmasının yapısını ve makinelerdeki yumurta kırım planlarını içermektedir. Kapasite, kırım oranı, briks değeri, makine kullanım oranı, sıvı oranı ve ihtiyaç duyulan ürün kısıtları altında toplam üretim miktarının maksimize edilmesi hedefi doğrultusunda elde edilen sonuçlar çalışmada verilmektedir

OPTIMIZATION FOR PRODUCTION PLANNING OF LIQUID EGG

Production planning becomes a difficult optimisation problem when the relationship between material, product and machine constraints is complicated. In this study, liquid egg production plan was optimized under specific production constraints. As a solution to the problem, a “Generalized Reduced Gradient”-based production planning model is developed, which considers the constraints encountered in real-life practice. The results yielded in the study in accordance with the objective of maximizing the total production under the constraints of capacity, breaking ratio, brix value, machine utilization ratio, liquid ratio and required product, are presented

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  • Bazaraa, M.S., Sherali, H.D. ve Shetty, C.M. (2006). Nonlinear Programming: Theory and Algorithms. Hoboken, NJ: John Wiley & Sons.
  • Boone, L.E. ve Kurtz, D.L. (2010). Contemporary Business. Hoboken, NJ: John Wiley & Sons.
  • Edgar, T.F. ve Himmelblau, D.M. (1989). Optimization of Chemical Process. New York: McGraw-Hill.
  • Fahim, S.R. ve Helmy, W. (2012). Optimal Study of Distributed Generation Impact on Electrical Distribution Networks Using GA and Generalized Reduced Gradient. International Conference on Engineering and Technology (ICET 2012), 10-11 Ekim 2012.
  • Faluyi, F. ve Arum, C. (2012). Design Optimization of Plate Girder Using Generalized Reduced Gradient and Constrained Artificial Bee Colony Algorithms. International Journal of Emerging Technology and Advanced Engineering, 2(7), 304-312.
  • Kao, C. (1998). Performance of Several Nonlinear Programming Software Packages on Microcomputers. Computers & Operations Research, 25(10), 807-816.
  • Kimball, D. (1991). Citrus Processing: Quality Control and Technology. New York: Springer Science.
  • Lasdon, L.S. ve Smith, S. (1992). Solving Sparse Nonlinear Programs Using GRG. ORSA Journal on Computing, 4(1), 2-15.
  • Lasdon L.S., Waren A., Jain A. ve Ratner, M. (1978). Design and Testing of a Generalized Reduced Gradient Code for Nonlinear Programming. ACM Transactions on Mathematical Software, 4(1), 34-50.
  • Lee, H.T., Chen, S.H. ve Kang, H.Y. (2004). A Study of Generalized Reduced Gradient Method with Different Search Directions. Journal of Measurement Management, 1(1), 25-38.
  • Mouatasim, A.E. (2010). Two-Phase Generalized Reduced Gradient Method for Constrained Global Optimization. Journal of Applied Mathematics, Article ID: 976529.
  • Prochaska, J.F, Carey, J.B. ve Shafer, J. (1996). The Effect of L-lysine Intake on Egg Component Yield and Composition in Laying Hens. Poultry Science, 75(10), 1268-77.
  • Rardin, R.L. (1998). Optimization in Operations Research, New Jersey: Prentice Hall.
  • Sharma, R. ve Glemmestad, B. (2013). On Generalized Reduced Gradient Method with Multi-start and Self-optimizing Control Structure for Gas Lift Allocation Optimization. Journal of Process Control, 23, 1129-1140.
  • Su, C.T. ve Lii, G.R. (1995). Reliability Optimization Design of Distribution Systems via Multi-level Hierarchical Procedures and Generalized Reduced Gradient Method, Energy Management and Power Delivery. Proceedings of EMPD '95 International Conference (21-23 Nov 1995), 180-185.
  • Sun, W. ve Yuan, Y. (2006). Optimization Theory and Methods: Nonlinear Programming. New York: Springer.
  • Ulucan, A. (2004). Yöneylem Araştırması: İşletmecilik Uygulamalı Bilgisayar Destekli Modelleme. Ankara: Siyasal Kitabevi.
  • Wolfe, P. (1963). Methods of Nonlinear Programming, Recent Advances in Mathematical Programming. New York: Mcgraw-Hill.
  • Yeniay, Ö. (2005). A Comparative Study on Optimization Methods for the Constrained Nonlinear Programming Problems. Mathematical Problems in Engineering, 2005(2), 165-173.