CGD Dry Port is a dry port that uses rail transportation mode as facilities of container transporter for the distribution of goods between regions. Control of Over Dimension Over Loaded (ODOL) has an impact on increasing demand for delivery the goods at the CGD Dry Port mainly demand delivery of goods. CGD Dry Port hasn’t been able to handle the demand delivery of cargo in full. This research aims to determine the factors that can affect the delivery volume and design improvement to improve the delivery volume using system dynamics simulation. The study commences by problem identification, model conceptual design, stock-flow diagram development, implement base case simulation, validate model, and improvement scenario plan. It is found that the delivery volume of KS products influences the Non-KS delivery volume. The total capacity of delivery is affected by the capacity of carriages container and delivery patterns. The GD 54 type carriage container has improved by our simulation. It was originally 48 tons, then becomes to 49 tons. Thus, we enhance the pattern of delivery into 20 times in a month, which has initially been 15 times. Based on the results of the improvement scenario, the average delivery volume of amount reaches 7476,48 tons/month in which the existing conditions amount only 3227 tons/month. Hence, the estimated income goes up until IDR 388.230.336/month in compare to the current revenue of IDR 164.917.505/month.

@inproceedings{oscm-2019-540,
  title={System Dynamic Modeling for Cargo Delivery Revenue Improvement in CGD Dry Port},
  year={2019},
  author={Asep Ridwan and Muhammad Iman Santoso and Ratna Ekawati and Reno Prasetyo},
  booktitle={Proceedings of the 9th International Conference on Operations and Supply Chain Management, Vietnam, 2019},
  doi={10.31387/oscm410181}
}

Asep Ridwan, Muhammad Iman Santoso, Ratna Ekawati, Reno Prasetyo (2019). System Dynamic Modeling for Cargo Delivery Revenue Improvement in CGD Dry Port. In Proceedings of the 9th International Conference on Operations and Supply Chain Management, Vietnam, 2019. https://doi.org/10.31387/oscm410181