Proceedings of the 7th International Conference on Applied Economics and Social Science (ICAESS 2025)

Balancing Stockout and Demurrage Risks in Fuel Supply Chains through Monte Carlo Simulation

Authors
Satriyo Hadi Wibowo1, *, Niniet Indah Arvitrida1
1Sepuluh Nopember Institute of Technology, Surabaya, 60111, Indonesia
*Corresponding author. Email: satriyo.wibowo@pertamina.com
Corresponding Author
Satriyo Hadi Wibowo
Available Online 13 February 2026.
DOI
10.2991/978-94-6463-990-2_9How to use a DOI?
Keywords
Inventory Management; Monte Carlo Simulation; Stockout Risk; Demurrage Costs; Fuel Supply Chain
Abstract

Fuel supply chains face critical challenges in balancing service reliability and cost efficiency, particularly in emerging markets with limited storage capacity. PT XYZ, a fuel distributor in Timor Leste, experienced two stockout incidents and two demurrage events in 2023, resulting in financial losses and operational disruptions. This study applies Monte Carlo simulation to model demand variability and lead time uncertainty for two key products (Gasoline RON 92 and Gasoil 0.05% Sulphur) over a 851-day horizon. Three inventory policies were evaluated: Min–Max, (s,Q), and (s,S), under three demand scenarios (normal, +20%, −15%). Performance indicators included total cost, service level, stockout days, and demurrage exposure. The results highlight significant trade-offs. The Min–Max policy consistently minimized stockout to below 1% but incurred high holding costs, reaching IDR 31.1 billion. The (s,Q) policy achieved the lowest total cost (IDR 143.1 billion) but suffered from high stockout risk, up to 35.25% under high demand. The (s,S) policy offered a balanced approach: for Gasoline RON 92 in the low-demand scenario, it completely eliminated stockout (0.00%) and demurrage, while in Gasoil under normal demand, stockout reached 25.38%. This study demonstrates that no single policy dominates across scenarios; instead, managers must weigh the trade-off between stockout and demurrage risks. The findings suggest that (s,S) provides a flexible baseline policy, with adaptive switching to Min–Max or (s,Q) depending on demand conditions. The results offer practical insights for fuel supply chain decision-makers facing uncertainty in demand and capacity constraints.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 7th International Conference on Applied Economics and Social Science (ICAESS 2025)
Series
Advances in Economics, Business and Management Research
Publication Date
13 February 2026
ISBN
978-94-6463-990-2
ISSN
2352-5428
DOI
10.2991/978-94-6463-990-2_9How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Satriyo Hadi Wibowo
AU  - Niniet Indah Arvitrida
PY  - 2026
DA  - 2026/02/13
TI  - Balancing Stockout and Demurrage Risks in Fuel Supply Chains through Monte Carlo Simulation
BT  - Proceedings of the 7th International Conference on Applied Economics and Social Science (ICAESS 2025)
PB  - Atlantis Press
SP  - 102
EP  - 116
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-990-2_9
DO  - 10.2991/978-94-6463-990-2_9
ID  - Wibowo2026
ER  -