OPTIMIZATION OF GASOLINE METHANOL ETHANOL (GME) SUPPLY CHAIN NETWORK DESIGN USING MIXED INTEGER LINEAR PROGRAMMING
Gasoline needs in Indonesia has been constantly increasing throughout the year. Domestic production capacity is relatively constant and could not fulfill all demands hence decided to import gasoline. To reduce gasoline import, the government is currently proposing Gasoline Methanol Ethanol (GME)...
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id-itb.:736552023-06-22T11:59:43ZOPTIMIZATION OF GASOLINE METHANOL ETHANOL (GME) SUPPLY CHAIN NETWORK DESIGN USING MIXED INTEGER LINEAR PROGRAMMING Firdaus, Azzimar Indonesia Final Project gasoline, gasoline methanol ethanol, supply chain network design, mixed integer linear programming, landed cost INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/73655 Gasoline needs in Indonesia has been constantly increasing throughout the year. Domestic production capacity is relatively constant and could not fulfill all demands hence decided to import gasoline. To reduce gasoline import, the government is currently proposing Gasoline Methanol Ethanol (GME) as a new energy source. GME is a blend of gasoline, methanol, and ethanol, mixed with specific compositions and additives. A key consideration for implementing GME is its supply chain. New GME supply chain network design (SCND) needs to be built. The approach to obtain an optimal GME SCND is to compare it with existing gasoline SCND. Landed cost can be used to compare both SCND performance. GME landed cost consists of gasoline cost, methanol cost, ethanol cost, additive cost, infrastructure cost, and conversion rate factor. Meanwhile, gasoline landed cost only consist of gasoline cost. In this research, mixed integer linear programming (MILP) is used to determine the SCND of GME. The objective of the model is to minimize the difference between the new GME landed cost and existing gasoline landed cost. All converted depot and amount of methanol & ethanol distributed from source to depot will be resulted after the model is solved. The result of the model shows that 0 out of 109 depots will be converted from gasoline to GME for both A6 and A20. Hence, 0 kL of methanol/ethanol will be distributed from certain source to depot. This implies that the GME landed cost is more expensive than the existing gasoline landed cost. The model is run with different scenario where conversion rate is neglected. The result for A6 is to convert 70 out of 109 depots in Indonesia with 53,58 USD/kL landed cost savings and for A20 is to convert 104 out of 109 depots in Indonesia with 454,52 USD/kL landed cost savings. text |
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Gasoline needs in Indonesia has been constantly increasing throughout the year.
Domestic production capacity is relatively constant and could not fulfill all
demands hence decided to import gasoline. To reduce gasoline import, the
government is currently proposing Gasoline Methanol Ethanol (GME) as a new
energy source. GME is a blend of gasoline, methanol, and ethanol, mixed with
specific compositions and additives. A key consideration for implementing GME
is its supply chain.
New GME supply chain network design (SCND) needs to be built. The approach
to obtain an optimal GME SCND is to compare it with existing gasoline SCND.
Landed cost can be used to compare both SCND performance. GME landed cost
consists of gasoline cost, methanol cost, ethanol cost, additive cost, infrastructure
cost, and conversion rate factor. Meanwhile, gasoline landed cost only consist of
gasoline cost. In this research, mixed integer linear programming (MILP) is used to
determine the SCND of GME. The objective of the model is to minimize the
difference between the new GME landed cost and existing gasoline landed cost. All
converted depot and amount of methanol & ethanol distributed from source to depot
will be resulted after the model is solved.
The result of the model shows that 0 out of 109 depots will be converted from
gasoline to GME for both A6 and A20. Hence, 0 kL of methanol/ethanol will be
distributed from certain source to depot. This implies that the GME landed cost is
more expensive than the existing gasoline landed cost. The model is run with
different scenario where conversion rate is neglected. The result for A6 is to convert
70 out of 109 depots in Indonesia with 53,58 USD/kL landed cost savings and for
A20 is to convert 104 out of 109 depots in Indonesia with 454,52 USD/kL landed
cost savings.
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format |
Final Project |
author |
Firdaus, Azzimar |
spellingShingle |
Firdaus, Azzimar OPTIMIZATION OF GASOLINE METHANOL ETHANOL (GME) SUPPLY CHAIN NETWORK DESIGN USING MIXED INTEGER LINEAR PROGRAMMING |
author_facet |
Firdaus, Azzimar |
author_sort |
Firdaus, Azzimar |
title |
OPTIMIZATION OF GASOLINE METHANOL ETHANOL (GME) SUPPLY CHAIN NETWORK DESIGN USING MIXED INTEGER LINEAR PROGRAMMING |
title_short |
OPTIMIZATION OF GASOLINE METHANOL ETHANOL (GME) SUPPLY CHAIN NETWORK DESIGN USING MIXED INTEGER LINEAR PROGRAMMING |
title_full |
OPTIMIZATION OF GASOLINE METHANOL ETHANOL (GME) SUPPLY CHAIN NETWORK DESIGN USING MIXED INTEGER LINEAR PROGRAMMING |
title_fullStr |
OPTIMIZATION OF GASOLINE METHANOL ETHANOL (GME) SUPPLY CHAIN NETWORK DESIGN USING MIXED INTEGER LINEAR PROGRAMMING |
title_full_unstemmed |
OPTIMIZATION OF GASOLINE METHANOL ETHANOL (GME) SUPPLY CHAIN NETWORK DESIGN USING MIXED INTEGER LINEAR PROGRAMMING |
title_sort |
optimization of gasoline methanol ethanol (gme) supply chain network design using mixed integer linear programming |
url |
https://digilib.itb.ac.id/gdl/view/73655 |
_version_ |
1822007171448045568 |