Automatic Configuration of Multi-Objective Local Search Algorithms for Permutation Problems,
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Aymeric Blot, Marie-Éléonore Kessaci, Laetitia Jourdan, and Holger H. Hoos,
In Evolutionary Computation, 27(1): 147–171, 2019.
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Survey and Unification of Local Search Techniques in Multi-Objective Metaheuristics,
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Aymeric Blot, Marie-Éléonore Kessaci, and Laetitia Jourdan,
In Journal of Heuristics, 24(6): 853–877, Springer, 2018.
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[preprint ]
Genetic Improvement of LLVM Intermediate Representation,
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William B. Langdon, Afnan Al-Subaihin, Aymeric Blot, and David Clark,
In EuroGP'23, Brno (Czech Republic), April 2023.
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Refining Fitness Functions for Search-Based Automated Program Repair — A Case Study with ARJA and ARJA-e,
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Giovani Guizzo, Aymeric Blot, James Callan, Justyna Petke, and Federica Sarro,
In SSBSE'21, LNCS 12914: 159–165, Springer, Bari (Italy), October 2021.
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Comparing Genetic Programming Approaches for Non-Functional Genetic Improvement — Case Study: Improvement of MiniSAT’s Running Time,
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Aymeric Blot and Justyna Petke,
In EuroGP'20, LNCS 12101: 68–83, Springer, Seville (Spain), April 2020.
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PyGGI 2.0: Language Independent Genetic Improvement Framework,
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Gabin An, Aymeric Blot, Justyna Petke, and Shin Yoo,
In ESEC/FSE'19, 1100–1104, ACM, Tallinn (Estonia), March 2019.
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Configuration of a Dynamic MOLS Algorithm for Bi-objective Flowshop Scheduling,
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Camille Pageau, Aymeric Blot, Holger H. Hoos, Marie-Éléonore Kessaci, and Laetitia Jourdan,
In EMO'19, LNCS 11411: 565–577, Springer, East Lansing (Michigan, USA), March 2019.
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Automatic Configuration of Multi-objective Optimization Algorithms — Impact of Correlation between Objectives,
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Aymeric Blot, Holger H. Hoos, Marie-Éléonore Kessaci, and Laetitia Jourdan,
In IEEE ICTAI'18, 571–578, IEEE, Volos (Greece), November 2018.
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New Initialisation Techniques for Multi-Objective Local Search — Application to the Bi-objective Permutation Flowshop Scheduling Problem,
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Aymeric Blot, Manuel López-Ibáñez, Marie-Éléonore Kessaci, and Laetitia Jourdan,
In PPSN'18, LNCS 11101: 323–334, Springer, Coimbra (Portugal), September 2018.
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[poster ](best paper nomination)
Adaptive Multi-Objective Local Search Algorithms for the Permutation Flowshop Scheduling Problem,
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Aymeric Blot, Marie-Éléonore Kessaci, Laetitia Jourdan, and Patrick De Causmaecker,
In LION'18, LNCS 11353: 241–256, Springer, Kalamata (Greece), June 2018.
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Automatic Design of Multi-objective Local Search Algorithms,
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Aymeric Blot, Laetitia Jourdan, and Marie-Éléonore Kessaci-Marmion,
In GECCO'17: 227–234, ACM, Berlin (Germany), July 2017.
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[slides ](best paper nomination)
Automatically Configuring Multi-objective Local Search using Multi-objective Optimisation,
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Aymeric Blot, Alexis Pernet, Laetitia Jourdan, Marie-Éléonore Kessaci-Marmion, and Holger H. Hoos,
In EMO'17, LNCS 10173: 61–76, Springer, Münster (Germany), March 2017.
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MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework,
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Aymeric Blot, Holger H. Hoos, Laetitia Jourdan, Marie-Éléonore Marmion, and Heike Trautmann,
In LION'16, LNCS 10079: 32–47, Springer, Ischia Island (Napoli, Italy), May 2016.
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Neutral but a Winner! How Neutrality helps Multiobjective Local Search Algorithms,
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Aymeric Blot, Hernán Aguirre, Clarisse Dhaenens, Laetitia Jourdan, Marie-Éléonore Marmion, and Kiyoshi Tanaka,
In EMO'15, LNCS 9018: 34–47, Springer, Guimarães (Portugal), March 2015.
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Neutrality in the Graph Coloring Problem,
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Marie-Éléonore Marmion, Aymeric Blot, Laetitia Jourdan, and Clarisse Dhaenens,
In LION'13, LNCS 7997: 125–130, Springer, Catania (Italy), January 2013.
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Genetically Improved Software with fewer Data Caches Misses,
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William B. Langdon, Justyna Petke, Aymeric Blot, and David Clark,
In GECCO'23 Compagnion, Lisbon (Spain), July 2023.
Evaluation of Genetic Improvement Tools for Improvement of Non-functional Properties of Software,
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Shengjie Zuo, Aymeric Blot, and Justyna Petke,
In the GI@GECCO'22 workshop, Boston (MA, USA), February 2022.
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[slides ](best paper award)
Using Genetic Improvement to Optimise Optimisation Algorithm Implementations,
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Aymeric Blot and Justyna Petke,
In ROADEF'22, Lyon (France), February 2022.
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Refining Fitness Functions for Search-Based Program Repair,
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Zhiqiang Bian, Justyna Petke, and Aymeric Blot,
In the APR@ICSE'21 workshop, Madrid (Spain), May 2021.
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Uniform Edit Selection for Genetic Improvement — Empirical Analysis of Mutation Operator Efficacy,
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Marta Smigielska, Aymeric Blot, and Justyna Petke,
In the GI@ICSE'21 workshop, Madrid (Spain), May 2021.
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Refining Fitness Functions in Test-Based Program Repair,
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Justyna Petke and Aymeric Blot,
In the APR@ICSE'20 workshop, Seoul (South Korea), July 2020.
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On Adaptive Specialisation in Genetic Improvement,
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Aymeric Blot and Justyna Petke,
In the GI@GECCO'19 workshop, GECCO'19 (Companion): 1703–1704, ACM, Prague (Czech Republic), July 2019.
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A Dynamic Algorithm Framework to Automatically Design a Multi-Objective Local Search,
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Camille Pageau, Aymeric Blot, Holger H. Hoos, Marie-Éléonore Kessaci, and Laetitia Jourdan,
In ROADEF'19, Le Havre (France), February 2019.
[hal ]
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Automatic Design of a Dynamic Multi-Objective Local Search Algorithm,
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Camille Pageau, Aymeric Blot, Holger H. Hoos, Marie-Éléonore Kessaci, and Laetitia Jourdan,
In the EvoML@PPSN'18 workshop, Coimbra (Portugal), September 2018.
AMH: a new Framework to Design Adaptive Metaheuristics,
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Aymeric Blot, Marie-Éléonore Kessaci-Marmion, and Laetitia Jourdan,
In MIC'17/MAEB'17, Barcelona (Spain), July 2017.
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AMH: une plate-forme pour le design et le contrôle automatique de métaheuristiques multi-objectif,
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Aymeric Blot, Marie-Éléonore Kessaci-Marmion, and Laetitia Jourdan,
In ROADEF'17, Metz (France), February 2017.
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MO-ParamILS: un framework multi-objectif pour la configuration automatique,
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Aymeric Blot and Holger H. Hoos,
In ROADEF'16, Compiègne (France), February 2016.
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Extension of NILS to the Multi-Objective Optimization — Case study: The Multi-Objective Permutation Flowshop Scheduling Problem,
Marie-Éléonore Marmion and Aymeric Blot,
In the SBLPA@PPSN'14 workshop, Ljubljana (Slovenia), October 2014.
Neutralité du problème de Coloration de Graphe,
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Marie-Éléonore Marmion, Aymeric Blot, Laetitia Jourdan, and Clarisse Dhaenens,
In ROADEF'13, Troyes (France), February 2013.
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Reinforcement Learning for Mutation Operator Selection in Automated Program Repair,
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Carol Hanna, Aymeric Blot, and Justyna Petke,
In CoRR abs/2306.05792, June 2023.
[arxiv ]
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GI Software with fewer Data Cache Misses,
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William B. Langdon, Justyna Petke, Aymeric Blot, and David Clark,
In CoRR abs/2304.03235, April 2023.
[arxiv ]
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A Comprehensive Survey of Benchmarks for Automated Improvement of Software's Non-Functional Properties,
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Aymeric Blot and Justyna Petke,
In CoRR abs/2212.08540, December 2022.
[arxiv ]
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[artefact ]
MAGPIE: Machine Automated General Performance Improvement via Evolution of Software,
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Aymeric Blot and Justyna Petke,
In CoRR abs/2208.02811, August 2022.
[arxiv ]
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Genetic Improvement @ ICSE 2020,
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William B. Langdon, Westley Weimer, Justyna Petke, Erik Fredericks, Seongmin Lee, Emily Winter, Michail Basios, Myra B. Cohen, Aymeric Blot, Markus Wagner, Bobby R. Bruce, Shin Yoo, Simos Gerasimou, Oliver Krauss, Yu Huang, and Michael Gerten,
In ACM SIGSOFT Software Engineering Notes 45 (4): 24–30, October 2020.
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Neutrality in the Graph Coloring Problem,
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Marie-Éléonore Marmion, Aymeric Blot, Laetitia Jourdan, and Clarisse Dhaenens,
In Rapport de Recherche INRIA, RR-8215, January 2013.
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Magpie — Machine Automated General Performance Improvement via Evolution of Software,
Presentation at the 63rd CREST Open Workshop (COW), London (United Kingdom), March 2023.
[slides ]
Software Improvement with Gin: A Case Study,
Paper presentation at the SSBSE'2019 Symposium, Tallinn (Estonia), August 2019.
Automatic Design of Multi-Objective Local Search Algorithms,
Presentation at the OPTIMA Seminar, Lille (France), November 2017.
Automatic Design of Multi-Objective Local Search Algorithms,
Presentation at the COSEAL Workshop, Brussels (Belgium), September 2017.
Reacting and Adapting to the Environment — Designing Autonomous Methods for Multi-Objective Combinatorial Optimisation,
Poster at the ATOM 2017 Summer School, Lille (France), June 2017.
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Tuning using Multiple Criteria — Forwarding more Information to the Configurator,
Presentation at the Dagstuhl Seminar 16412, Schloss Dagstuhl (Germany), October 2016.
How to React and Adapt to the Environment — Designing Autonomous Methods for Multi-objective Combinatorial Optimization,
Presentation at the ORKAD Symposium, Lille (France), June 2016.
MO-ParamILS — A Multi-objective Iterated Local Search for Automatic Algorithm Configuration,
Presentation at the EWG Data Science for Optimisation Foundational Meeting, Leuven (Belgium), April 2016.
Analyse de paysage et algorithmes de recherche locale en multi-objectif,
Presentation at the ATOM Annual Meeting, Paris (France), June 2014.