Jacobus van der Linden

Jacobus van der Linden

Short name: Koos

PhD student

Publications

You can also find my articles on my Google Scholar profile.

Highlights

Necessary and Sufficient Conditions for Optimal Decision Trees Using Dynamic Programming

Published in Advances in NeurIPS-23, 2023

We prove necessary and sufficient conditions for the use of DP for optimal decision trees and provide a framework STreeD that can optimize trees for a variety of objectives and constraints.

Recommended citation: Van der Linden, J. G. M., de Weerdt, M. M., & Demirović, E. (2023). "Necessary and Sufficient Conditions for Optimal Decision Trees Using Dynamic Programming." Advances in NeurIPS-23, 9173-9212.
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Published Articles

How to Discover Short, Shorter, and the Shortest Proofs of Unsatisfiability: A Branch-and-Bound Approach for Resolution Proof Length Minimization

Published in Journal of Artificial Intelligence Research, 2026

A branch-and-bound approach to minimizing the clause length of a resolution proof of unsatisfiability

Recommended citation: Sidorov, K., Van der Linden, K., Correia, G. H. A., De Weerdt, M. & Demirović, E. (2026) "How to Discover Short, Shorter, and the Shortest Proofs of Unsatisfiability: A Branch-and-Bound Approach for Resolution Proof Length Minimization" Journal of Artificial Intelligence Research 86, Article 54, 39 pages.
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Optimal Classification Trees for Continuous Feature Data Using Dynamic Programming with Branch-and-Bound

Published in Proceedings of AAAI-25, 2025

ConTree computes optimal binary classification trees on datasets with continuous features using dynamic programming with branch-and-bound.

Recommended citation: Brita, C. E., van der Linden, J. G. M., & Demirović, E. (2025). "Optimal Classification Trees for Continuous Feature Data Using Dynamic Programming with Branch-and-Bound." Proceedings of AAAI-25, 11131-11139.
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Piecewise Constant and Linear Regression Trees: An Optimal Dynamic Programming Approach

Published in Proceedings of ICML-24, 2024

We use DP to generate optimal regression trees with constant and (simple) linear regression models in the leaf node. Our method improves scalability by one or more orders of magnitude in comparison to the state-of-the-art.

Recommended citation: Van den Bos, M., van der Linden, J. G. M., & Demirović, E. (2024). "Piecewise Constant and Linear Regression Trees: An Optimal Dynamic Programming Approach." Proceedings of ICML-24.
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TORS: A Train Unit Shunting and Servicing Simulator

Published in Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2021

We developed TORS, an event-based simulator for the Train Unit Shunting and Servicing problem, which enables research on realistic applications of multi-agent pathfinding by providing users with a state, feasible actions, and real-time outcome calculations.

Recommended citation: Van der Linden, J. G. M., Mulderij, J., Huisman, B., den Ouden, J. W., van den Akker, M., Hoogeveen, H., & de Weerdt, M. M. (2021). "TORS: A Train Unit Shunting and Servicing Simulator." Proceedings of AAMAS-21, 1773-1775.
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Stochastic bidding of volume and price in constrained energy and reserve markets

Published in Electric Power Systems Research, 2021

We compare state-of-the-art methods for bidding strategies in the day-ahead and reserve markets for large fleets of flexible loads like EVs.

Recommended citation: Romero, N., Van der Linden, K., Morales-España, G., & de Weerdt, M., (2021). "Stochastic bidding of volume and price in constrained energy and reserve markets." Electric Power Systems Research 191, 106868.
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Complexity of Scheduling Charging in the Smart Grid

Published in Proceedings of IJCAI-18, 2018

For about 20 variants of charging scheduling problems, we show that the problem is either in P or weakly NP-hard and we show that 10 variants are strongly NP-hard.

Recommended citation: De Weerdt, M., Albert, M., Conitzer, V., & van der Linden, K. (2018). "Complexity of Scheduling Charging in the Smart Grid." Proceedings of IJCAI-18, 4736-4742.
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Optimal Non-Zero Price Bids for EVs in Energy and Reserves Markets using Stochastic Optimization

Published in Proceedings of the 15th International Conference on the European Energy Market (EEM), 2018

We contribute a stochastic optimization method for EV aggregators that models uncertainty in imbalance prices, reserve prices, and reserve acceptance probabilities, enabling optimal charging and discharging strategies that outperform deterministic and quantity-only bid approaches by lowering costs.

Recommended citation: Van der Linden, K., de Weerdt, M., & Morales-España, G. (2018). "Optimal Non-Zero Price Bids for EVs in Energy and Reserves Markets using Stochastic Optimization." Proceedings of the 15th International Conference on the European Energy Market (EEM).
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Other work

Train Unit Shunting and Servicing: A Real-Life Application of Multi-Agent Path Finding

ArXiv Preprint, 2020

We analyze the potential of extending the multi-agent path finding model to provide bounds for the train unit shunting and service problem, which helps to evaluate heuristic solutions and inform investment decisions on yard capacity.

Recommended citation: Mulderij, J., Huisman, B., Tönissen, D., van der Linden, K., & de Weerdt, M. (2020). "Train Unit Shunting and Servicing: A Real-Life Application of Multi-Agent Path Finding." arXiv preprint, arXiv:2006.10422.
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Decision Diagrams for Decomposed Mixed Integer Linear Programs

Master Thesis, 2017

Optimizing mixed-integer linear programs with decision diagrams by decomposing the problem using benders decomposition.

Recommended citation: Van der Linden, K. (2017). Decision Diagrams for Decomposed Mixed Integer Linear Programs [Master thesis, Delft University of Technology]. TU Delft Research Repository.
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