Supply Chain Optimization Model for Fresh Cow's Milk to Reduce Carbon Emissions and Food Waste


Model Optimasi Rantai Pasok Susu Sapi Segar untuk Mereduksi Emisi Karbon dan Food Waste


  • (1) * Nofariza Aulia Jeremi            Teknik Sistem dan Industri, Fakultas Teknologi Industri Rekayasa Sistem, Institut Teknologi Sepuluh Nopember  
            Indonesia

  • (2)  Iwan Vanany            Teknik Sistem dan Industri, Fakultas Teknologi Industri Rekayasa Sistem, Institut Teknologi Sepuluh Nopember  
            Indonesia

    (*) Corresponding Author

Abstract

The food and beverage industry occupies an important position in Indonesia, with growth in 5 (five) years, an average of 8.16%. In 2022, the food and beverage industry contributed more than one-third or 37.77% of the GDP of the non-oil and gas processing industry. However, growth considered positive for the economy is actually a threat to the environment. With the high demand for food, food waste and carbon emissions from all food supply chain (FSC) activities increase. This study raises a case of a dairy product processing supply chain in the West Java region with multiple milk suppliers (KUD Susu), a single processing production plant, multi distributors, and multi-consumer retail with multi-echelon, multi-period, and multi-product friendly conditions. Environment by considering food waste and carbon emissions as a function of the objective model. In solving this problem, the Mixed Integer Linear Programming (MILP) model is used in modeling supply chain processes to optimize total cost/TC, total food waste/TFW, and total carbon emissions/TCE. The results of the completion of the research showed a total cost of IDR 18,036,770,000, a total food waste/TFW of 21,734 liters, and a total carbon emission/TCE of 109,526 l.CO2-eq.

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Published
2023-07-10
 
How to Cite
Jeremi, N. A., & Vanany, I. (2023). Supply Chain Optimization Model for Fresh Cow’s Milk to Reduce Carbon Emissions and Food Waste. PROZIMA (Productivity, Optimization and Manufacturing System Engineering), 7(1), 46-58. https://doi.org/10.21070/prozima.v7i1.1617
Section
Articles