Geoffrey De Smet

Geoffrey De Smet

Ghent, Flemish Region, Belgium
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I am a world-renowed expert in automated planning of complex schedules and the AI…

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    Ghent, Flemish Region, Belgium

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    Ghent, Flemish Region, Belgium

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    Gent Area, Belgium

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    Gent Area, Belgium

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    Gent Area, Belgium

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    Ghent Area, Belgium

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    Gent Area, Belgium

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    Belgien

Licenses & Certifications

Publications

  • Multithreaded incremental solving for local search based metaheuristics with step chasing

    Proceedings of the 13th International Conference on the Practice and Theory of Automated Timetabling - PATAT 2021: Volume I

    This work introduces a multithreaded solving methodology for lo-
    cal search based metaheuristics. It runs a single local search that spreads move
    evaluations across multiple threads. To preserve incremental score calculation
    (delta evaluation) capabilities, which are essential for the performance of lo-
    cal search methods, the child threads reproduce the step of the main thread
    in a method we named step chasing. The proposed method is implemented
    within OptaPlanner, a…

    This work introduces a multithreaded solving methodology for lo-
    cal search based metaheuristics. It runs a single local search that spreads move
    evaluations across multiple threads. To preserve incremental score calculation
    (delta evaluation) capabilities, which are essential for the performance of lo-
    cal search methods, the child threads reproduce the step of the main thread
    in a method we named step chasing. The proposed method is implemented
    within OptaPlanner, a Java-based open source solver, and can thus be used
    by anyone. The effectiveness of the method is demonstrated using three meta-
    heuristics (Tabu Search, Simulated Annealing, Late Acceptance) on four dif-
    ficult combinatorial optimization problems: the nurse rostering problem, the
    vehicle routing problem, the curriculum course timetabling problem and the
    cloud balancing problem. Extensive experiments are performed using up to
    16 threads with a total of 5550 runs, with significant speedups realized when
    more threads are available to the solver. All results are compared with a sin-
    gle threaded implementation, as well as a multi-walk approach. The greatest
    speedups take place with respect to the nurse rostering problem.

    Other authors
    See publication

Patents

  • Limited duration supply for heuristic algorithms

    Issued U.S. Patent No 11,200,296

  • Multi-threaded constraint satisfaction solver

    Issued U.S. Patent No. 10,509,654

Projects

  • OptaPlanner

    - Present

    OptaPlanner optimizes business resource usage. Every organization faces planning problems: provide products or services with a limited set of constrained resources (employees, assets, time and money). OptaPlanner optimizes such planning to do more business with less resources.

    OptaPlanner is a lightweight, embeddable planning engine written in Java™. It helps normal Java™ programmers solve constraint satisfaction problems efficiently. Under the hood, it combines optimization heuristics…

    OptaPlanner optimizes business resource usage. Every organization faces planning problems: provide products or services with a limited set of constrained resources (employees, assets, time and money). OptaPlanner optimizes such planning to do more business with less resources.

    OptaPlanner is a lightweight, embeddable planning engine written in Java™. It helps normal Java™ programmers solve constraint satisfaction problems efficiently. Under the hood, it combines optimization heuristics and metaheuristics with very efficient score calculation.

    Other creators
    See project

Test Scores

  • Sun Certified Web Component Developer for Java 2 Platform, Enterprise Edition

    Score: 94%

  • Sun Certified Programmer for the Java 2 Platform 1.4

    Score: 95%

Languages

  • Englisch

    Full professional proficiency

  • Dutch

    Native or bilingual proficiency

  • French

    Limited working proficiency

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