PERANCANGAN RANTAI PASOK BIOETANOL DENGAN BAHAN BAKU TANDAN KOSONG KELAPA SAWIT DI INDONESIA

Energy problem has become a global issue in many countries around the world, including in Indonesia. Rising living standards lead to an increase in the nation's energy needs are particularly dominated by the transport sector. The increase in the energy requirements result in the reduction in...

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Main Authors: WINARDO, DINAN, Sopha, Bertha Maya
格式: Theses and Dissertations NonPeerReviewed
出版: [Yogyakarta] : Universitas Gadjah Mada 2014
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在線閱讀:https://repository.ugm.ac.id/131054/
http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=71495
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總結:Energy problem has become a global issue in many countries around the world, including in Indonesia. Rising living standards lead to an increase in the nation's energy needs are particularly dominated by the transport sector. The increase in the energy requirements result in the reduction in the supply of domestic crude oil. To limit the use of fuel oil in Indonesia, the government has made a strategic move to use alternative fuels as mixing one of them is the use of bioethanol as a mixture of the fuel oil. To support the government's efforts be required an analysis of the bioethanol plant site selection and daily production capacity in Indonesia to create a network of sustainable bioethanol supply chain. The mathematical model is constructed mixed integer linear programming model with the characteristics of a deterministic system. The parameters used in the optimization model is the transport distance, demand, capacity of plant, the cost of fuel, investment and operational costs. The objective function in this model is to minimize the overall logistics costs. Furthermore, a mathematical model was built by using the add-in CPLEX. The results obtained in the form of a decision to open 37 locations bioethanol plant of 44 potential sites bioethanol plant in Indonesia with a total cost of 4.2 billion dollars. While the sensitivity analysis results in which all model parameters affect the decision opening the factory. While bioethanol demand parameters provide the most significant effect on the overall change in the total cost.