This repository contains the code, data, and materials accompanying my thesis:
“Stochastic Optimization of a Container Terminal and Energy Markets.”
The work investigates how stochastic optimization can improve container terminal operations under uncertainty from fluctuating energy markets. It combines decision-making models, simulation, and optimization to evaluate operational and energy-related trade-offs.
🧾 The full paper is published in the Journal of Cleaner Production:
👉 Read on ScienceDirect
Container terminals increasingly face operational challenges related to:
- Variability in vessel arrivals and handling times
- Fluctuating electricity prices and renewable energy integration
- Environmental and efficiency objectives
This thesis develops and evaluates several optimization formulations that integrate stochastic modeling and energy market uncertainty. The study compares deterministic, average-based, and reactive strategies for scheduling and resource allocation.
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CT+EM_6_solve.ipynb
The main script of the thesis.- Collects all input data
- Builds the stochastic optimization model
- Solves it under several uncertainty formulations (deterministic, weighted, and reactive)
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CT+EM_7_analyse.ipynb
Analysis notebook containing visualization, result aggregation, and scenario comparison. -
Day-ahead Prices_*.csv
Historical day-ahead electricity prices (2015–2023), used to represent uncertainty in energy markets.
If you use or reference this work, please cite the published article:
Stochastic Optimization of a Container Terminal and Energy Markets Journal of Cleaner Production, 2025. https://www.sciencedirect.com/science/article/pii/S0959652625017330
BibTeX:
@article{Stoter2025, title={Stochastic optimization of a container terminal and energy markets}, author={Jasper Stoter}, journal={Journal of Cleaner Production}, year={2025}, publisher={Elsevier}, url={https://www.sciencedirect.com/science/article/pii/S0959652625017330} }
© 2025 Jasper Stoter. All rights reserved.