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    Item type:Publication, Access status: without files ,
    A comparison of repositioning and scheduling algorithms for the ride-hailing problem
    (Springer, 2026-08)
    Paul, Lauren
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    Hübner, Sebastian
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    Plump, Christina
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    Berger, Bernhard J.
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    Drechsler, Rolf
    The Ride-Hailing Problem is an online optimization challenge that coordinates a fleet of vehicles to serve requests revealed over time. The problem is NP-hard, and many solution approaches use stochastic or machine-learning based algorithms, which perform well but are difficult to interpret. We study the trade-offs between performance and explainability. Our results show that greedy assignment consistently outperforms more complex methods, indicating that explainability need not come at the cost of efficiency. We also find that the effectiveness of repositioning strategies strongly depends on demand patterns, highlighting the value of context-aware policies.
    Publicationtype: Conference Paper
      7
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    EvoAl - codeless domain-optimisation
    (Association for Computing Machinery (ACM), 2024-07-14)
    Berger, Bernhard Johannes
    ;
    Plump, Christina
    ;
    Paul, Lauren
    ;
    Drechsler, Rolf
    Applying optimisation techniques such as evolutionary computation to real-world tasks often requires significant adaptation. However, specific application domains do not typically demand major changes to existing optimisation methods. The decisive aspect is the inclusion of domain knowledge and configuration of established techniques to suit the problem. Separating the optimisation technique from the domain knowledge offers several advantages: First, it allows updating domain knowledge without necessitating reimplementation. Second, it improves identification and comparison of the optimisation methods employed. We present EvoAl, an open-source data-science research tool suite that focuses on optimisation research for real-world problems. EvoAl implements the separation of domain-knowledge and detaches implementation from configuration, facilitating optimisation with little programming effort, allowing direct comparability with other approaches (using EvoAl), and ensuring reproducibility. EvoAl also includes options for surrogate models, data models for complex search spaces, data validation, and benchmarking options for optimisation researchers.
    Publicationtype: Conference Paper
      15