ROAD NETWORK RESTORATION MODEL FOR HUMANITARIAN LOGISTICS DURING DISASTER RESPONSE STAGE
The rescue process is a top priority in the emergency response stage of an earthquake disaster. One of the activities carried out as a rescue effort in the emergency response stage is humanitarian logistics activities. However, humanitarian logistics has the challenge of operating within a limite...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/59605 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | The rescue process is a top priority in the emergency response stage of an
earthquake disaster. One of the activities carried out as a rescue effort in the
emergency response stage is humanitarian logistics activities. However,
humanitarian logistics has the challenge of operating within a limited road network
due to the damage caused by the disaster. For this reason, this study aims to model
the optimization of road network restoration that considers the needs of
humanitarian logistics at the disaster emergency response stage.
Minimization of restoration time allocation of each node is used as the objective
function of the developed road network restoration optimization model, with
constraints including the restoration time limit, the availability of restoration unit
resources, and network accessibility at both the route and network levels. The data
used in this study is the Lombok Island’s road network data along with data on the
impact of the Lombok earthquake in 2018. The main algorithm used in the model is
the Hungarian algorithm for time allocation, with the Dijkstra algorithm used in
the identification process of the shortest route. The model is tested with a
hypothetical road network consisting of 16 nodes before being applied to the
Lombok network consisting of 88 nodes. The tool used for the modeling process is
the Python programming language.
Based on the results of the model running, the developed optimization model is able
to obtain an optimal solution that satisfies all constraints in a relatively fast time,
which is 1.37 seconds. The results of the sensitivity analysis on the capacity of the
restoration unit and the vehicle speed of the restoration unit show that there is no
change in the list of repaired nodes. However, increasing restoration unit capacity
and restoration unit vehicle speed had the effect of suppressing the total restoration
time spent.
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