A unified race algorithm for offline parameter tuning

Tim Van Dijk, Martijn Mes, Marco Schutten, Joaquim Antonio Gromicho Dos Santos

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review


This paper proposes uRace, a unified race algorithm for efficient offline parameter tuning of deterministic algorithms. We build on the similarity between a stochastic simulation environment and offline tuning of deterministic algorithms, where the stochastic element in the latter is the unknown problem instance given to the algorithm. Inspired by techniques from the simulation optimization literature, uRace enforces fair comparisons among parameter configurations by evaluating their performance on the same training instances. It relies on rapid statistical elimination of inferior parameter configurations and an increasingly localized search of the parameter space to quickly identify good parameter settings. We empirically evaluate uRace by applying it to a parameterized algorithmic framework for loading problems at ORTEC, a global provider of software solutions for complex decision-making problems, and obtain competitive results on a set of practical problem instances from one of the world's largest multinationals in consumer packaged goods.

Original languageEnglish
Title of host publicationProceedings of the 2014 Winter Simulation Conference, WSC 2014
PublisherInstitute of Electrical and Electronics Engineers, Inc.
Number of pages12
ISBN (Electronic)9781479974863
Publication statusPublished - 2015
Event2014 Winter Simulation Conference, WSC 2014 - Savannah, United States
Duration: 7 Dec 201410 Dec 2014


Conference2014 Winter Simulation Conference, WSC 2014
Country/TerritoryUnited States


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