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- W4384789213 abstract "In our society, sustainability and global responsibility concepts have been gaining in importance over the years. For the manufacturing companies and supply chains there is a direct impact on their benefits, not only through an increasing demand of sustainable products, but also trough the regulations that aim to reduce the total emissions over the years. Moreover, due to the current political situation, the prices of energy could jeopardize many companies, whose production is no longer profitable. For all these reasons, it is more important than ever to apply a holistic view in the design of supply chains and ensure a model that considers risk management. Our case-study is a petrochemical three echelon supply chain in Europe, where we incorporate the cap-and-trade model from the European Union emissions Trading System, to directly link the emissions associated to consumption of raw material, energy consumption and transportation to the total benefit of the supply chain. We present an optimal design of a supply chain facing uncertainty in energy prices, which is modelled by fitting historical data in an ARIMA model. It involves the solution of a multi-objective multi-period mixed integer linear program that was implemented in Python using Pyomo and solved using IBMs CPLEX solver." @default.
- W4384789213 created "2023-07-20" @default.
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- W4384789213 date "2023-01-01" @default.
- W4384789213 modified "2023-10-17" @default.
- W4384789213 title "Multi-objective sustainable supply chain design under uncertainty in energy price" @default.
- W4384789213 cites W1982280427 @default.
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- W4384789213 doi "https://doi.org/10.1016/b978-0-443-15274-0.50547-3" @default.
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