The irace Package: Iterated Race for Automatic Algorithm Configuration. The irace package implements the iterated racing procedure, which is an extension of the Iterated F-race procedure. Its main purpose is to automatically configure optimization algorithms by finding the most appropriate settings given a set of instances of an optimization problem. It builds upon the race package by Birattari and it is implemented in R. Keywords: automatic configuration, offline tuning, parameter tuning, racing, F-race. Relevant literature: Manuel López-Ibáñez, Jérémie Dubois-Lacoste, Thomas Stützle, and Mauro Birattari. The irace package, Iterated Race for Automatic Algorithm Configuration. Technical Report TR/IRIDIA/2011-004, IRIDIA, Université libre de Bruxelles, Belgium, 2011.

References in zbMATH (referenced in 142 articles )

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  1. Corazza, Marco; di Tollo, Giacomo; Fasano, Giovanni; Pesenti, Raffaele: A novel hybrid PSO-based metaheuristic for costly portfolio selection problems (2021)
  2. de Oliveira, Sabrina M.; Bezerra, Leonardo C. T.; Stützle, Thomas; Dorigo, Marco; Wanner, Elizabeth F.; de Souza, Sérgio R.: A computational study on ant colony optimization for the traveling salesman problem with dynamic demands (2021)
  3. Diaz, Juan Esteban; López-Ibáñez, Manuel: Incorporating decision-maker’s preferences into the automatic configuration of bi-objective optimisation algorithms (2021)
  4. Fernandes, Islame F. C.; Goldbarg, Elizabeth F. G.; Maia, Silvia M. D. M.; Goldbarg, Marco C.: Multi- and many-objective path-relinking: a taxonomy and decomposition approach (2021)
  5. Fink, Andreas; Gerhards, Patrick: Negotiation mechanisms for the multi-agent multi-mode resource investment problem (2021)
  6. Gliesch, Alex; Ritt, Marcus: A hybrid heuristic for the maximum dispersion problem (2021)
  7. Grimme, Christian; Kerschke, Pascal; Aspar, Pelin; Trautmann, Heike; Preuss, Mike; Deutz, André H.; Wang, Hao; Emmerich, Michael: Peeking beyond peaks: challenges and research potentials of continuous multimodal multi-objective optimization (2021)
  8. Jesus, Alexandre D.; Paquete, Luís; Liefooghe, Arnaud: A model of anytime algorithm performance for bi-objective optimization (2021)
  9. Limbeck, Jan; Bisdom, Kevin; Lanz, Fabian; Park, Timothy; Barbaro, Eduardo; Bourne, Stephen; Kiraly, Franz; Bierman, Stijn; Harris, Chris; Nevenzeel, Keimpe; den Bezemer, Taco; van Elk, Jan: Using machine learning for model benchmarking and forecasting of depletion-induced seismicity in the Groningen gas field (2021)
  10. Mathlouthi, Ines; Gendreau, Michel; Potvin, Jean-Yves: A metaheuristic based on tabu search for solving a technician routing and scheduling problem (2021)
  11. Máximo, Vinícius R.; Nascimento, Mariá C. V.: A hybrid adaptive iterated local search with diversification control to the capacitated vehicle routing problem (2021)
  12. Melo, Rafael A.; Queiroz, Michell F.; Ribeiro, Celso C.: Compact formulations and an iterated local search-based matheuristic for the minimum weighted feedback vertex set problem (2021)
  13. Nof, Yair; Strichman, Ofer: Real-time solving of computationally hard problems using optimal algorithm portfolios (2021)
  14. Pan, Binbin; Zhang, Zhenzhen; Lim, Andrew: Multi-trip time-dependent vehicle routing problem with time windows (2021)
  15. Pan, Binbin; Zhang, Zhenzhen; Lim, Andrew: A hybrid algorithm for time-dependent vehicle routing problem with time windows (2021)
  16. Rodríguez, Alma; Camarena, Octavio; Cuevas, Erik; Aranguren, Itzel; Valdivia-G, Arturo; Morales-Castañeda, Bernardo; Zaldívar, Daniel; Pérez-Cisneros, Marco: Group-based synchronous-asynchronous grey wolf optimizer (2021)
  17. Santos, Vinícius Gandra Martins; Carvalho, Marco Antonio Moreira de: Tailored heuristics in adaptive large neighborhood search applied to the cutwidth minimization problem (2021)
  18. Sousa, Marques Moreira de; González, Pedro Henrique; Ochi, Luiz Satoru; Martins, Simone de Lima: A hybrid iterated local search heuristic for the traveling salesperson problem with hotel selection (2021)
  19. Theresa Eimer, André Biedenkapp, Maximilian Reimer, Steven Adriaensen, Frank Hutter, Marius Lindauer: DACBench: A Benchmark Library for Dynamic Algorithm Configuration (2021) arXiv
  20. Tran, Duy Hoang; Babaki, Behrouz; Van Daele, Dries; Leyman, Pieter; De Causmaecker, Patrick: Local search for constrained graph clustering in biological networks (2021)

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