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An optimization approach for brass casting blending problem under aletory and epistemic uncertainties

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  • SakallI, Ümit Sami
  • Baykoç, Ömer Faruk

Abstract

A critical process in brass casting is the determination of the materials and their quantities to be added into the blend. The reason of being critical is the uncertainty about metal percentages in scrap raw materials. In this paper, the aleatory and epistemic uncertainties, which are modeled by using probability and possibility theory, respectively, have been handled simultaneously in a blending optimization problem for brass casting and a solution approach that transforms the possibilistic uncertainties into probabilistic ones is proposed. A numerical example is performed by the data supplied from MKE brass factory in Turkey. The results of the example have showed that the proposed approach can be effectively used for solving blending problem including aleatory and epistemic uncertainties in brass casting and other scrap based production process.

Suggested Citation

  • SakallI, Ümit Sami & Baykoç, Ömer Faruk, 2011. "An optimization approach for brass casting blending problem under aletory and epistemic uncertainties," International Journal of Production Economics, Elsevier, vol. 133(2), pages 708-718, October.
    • Handle: RePEc:eee:proeco:v:133:y:2011:i:2:p:708-718
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    Cited by:

    1. Reinol Josef Compañero & Andreas Feldmann & Peter Samuelsson & Anders Tilliander & Pär Göran Jönsson & Rutger Gyllenram, 2023. "Appraising the value of compositional information and its implications to scrap-based production of steel," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(3), pages 463-480, September.
    2. Djeumou Fomeni, Franklin, 2018. "A multi-objective optimization approach for the blending problem in the tea industry," International Journal of Production Economics, Elsevier, vol. 205(C), pages 179-192.
    3. Siemon, Michel & Schiffer, Maximilian & Walther, Grit, 2021. "Integrated purchasing and production planning for a non-Ferrous metal production network," Omega, Elsevier, vol. 98(C).
    4. Bariş Keçeci & Yusuf Tansel Iç & Ergün Eraslan, 2019. "Development of a Spreadsheet DSS for Multi-Response Taguchi Parameter Optimization Problems Using the TOPSIS, VIKOR, and GRA Methods," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(05), pages 1501-1531, September.
    5. Aydoğan Baş & Burak Birgören & Ümit Sami Sakalli, 2024. "Obtaining a Multi-Factor Optimum Blend Using Scrap within the Scope of Sustainable and Environmentally Friendly Steel Production: Application in a Steel-Casting Company," Sustainability, MDPI, vol. 16(11), pages 1-18, May.

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