Browse by UCL people
Group by: Type | Date
Number of items: 23.
Article
Blot, A;
Kessaci, M-É;
Jourdan, L;
Hoos, HH;
(2019)
Automatic Configuration of Multi-Objective Local Search Algorithms for Permutation Problems.
Evolutionary Computation
, 27
(1)
pp. 147-171.
10.1162/evco_a_00240.
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Blot, A;
Kessaci, MÉ;
Jourdan, L;
(2018)
Survey and unification of local search techniques in metaheuristics for multi-objective combinatorial optimisation.
Journal of Heuristics
, 24
(6)
pp. 853-877.
10.1007/s10732-018-9381-1.
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Blot, A;
Petke, J;
(2021)
Empirical Comparison of Search Heuristics for Genetic Improvement of Software.
IEEE Transactions on Evolutionary Computation
10.1109/TEVC.2021.3070271.
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Proceedings paper
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An, G;
Blot, A;
Petke, J;
Yoo, S;
(2019)
PyGGI 2.0: Language independent genetic improvement framework.
In:
Proceedings of the 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering 2019.
(pp. pp. 1100-1104).
ACM: New York (NY), USA.
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Bian, Z;
Blot, A;
Petke, J;
(2021)
Refining Fitness Functions for Search-Based Program Repair.
In:
2021 IEEE/ACM International Workshop on Automated Program Repair (APR).
IEEE: Madrid, Spain (held virtually).
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Blot, Aymeric;
Petke, Justyna;
(2022)
Using Genetic Improvement to Optimise Optimisation Algorithm Implementations.
In:
Proceedings of the 23rd annual congress of the French Society for Operational Research and Decision Support ROADEF'2022.
ROADEF: Lyon, France.
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Blot, A;
(2019)
Fuzzy Edit Sequences in Genetic Improvement.
In:
Proceedings of the 2019 IEEE/ACM International Workshop on Genetic Improvement (GI).
(pp. pp. 30-31).
IEEE
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Blot, A;
Hoos, HH;
Kessaci, M-E;
Jourdan, L;
(2018)
Automatic Configuration of Bi-objective Optimisation Algorithms: Impact of Correlation between Objectives.
In:
30th IEEE International Conference on Tools with Artificial Intelligence Proceedings.
(pp. pp. 571-578).
IEEE
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Blot, A;
Jourdan, L;
Kessaci, M;
(2017)
Automatic design of multi-objective local search algorithms case study on a bi-objective permutation flowshop scheduling problem.
In:
(Proceedings) GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference.
(pp. pp. 227-234).
ACM: New York, NY, USA.
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Blot, A;
Kessaci, MÉ;
Jourdan, L;
De Causmaecker, P;
(2018)
Adaptive multi-objective local search algorithms for the permutation flowshop scheduling problem.
In:
International Conference on Learning and Intelligent Optimization.
(pp. pp. 241-256).
Springer: Cham, Switzerland.
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Blot, A;
López-Ibáñez, M;
Kessaci, MÉ;
Jourdan, L;
(2018)
New initialisation techniques for multi-objective local search: Application to the bi-objective permutation flowshop.
In:
Parallel Problem Solving from Nature – PPSN XV.
(pp. pp. 323-334).
Springer: Cham, Switzerland.
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Blot, A;
Pernet, A;
Jourdan, L;
Kessaci-Marmion, M;
Hoos, H;
(2017)
Automatically configuring multi-objective local search using multi-objective optimisation.
In:
Evolutionary Multi-Criterion Optimization.
(pp. pp. 61-76).
Springer: Cham, Switzerland.
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Blot, A;
Petke, J;
(2020)
Stack-Based Genetic Improvement.
In:
ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops.
(pp. pp. 289-290).
ACM
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Blot, A;
Petke, J;
(2020)
Synthetic Benchmarks for Genetic Improvement.
In:
ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops.
(pp. pp. 287-288).
ACM
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Blot, A;
Petke, J;
(2020)
Comparing Genetic Programming Approaches for Non-functional Genetic Improvement.
In: Hu, T and Lourenço, N and Medvet, E and Divina, F, (eds.)
Genetic Programming.
(pp. pp. 68-83).
Springer Nature: Cham, Switzerland.
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Blot, A;
Petke, J;
(2019)
On Adaptive Specialisation in Genetic Improvement.
In:
Proceedings of the 2019 Genetic and Evolutionary Computation Conference (GECCO).
(pp. pp. 1703-1704).
Association for Computing Machinery (ACM): New York, NY, USA.
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Guizzo, G;
Blot, A;
Callan, J;
Petke, J;
Sarro, F;
(2021)
Refining Fitness Functions for Search-Based Automated Program Repair: A Case Study with ARJA and ARJA-e.
In: Sarro, F and Deb, K, (eds.)
SSBSE: International Symposium on Search Based Software Engineering.
Springer: Cham, Switzerland.
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Langdon, WB;
Weimer, W;
Petke, J;
Fredericks, E;
Lee, S;
Winter, E;
Basios, M;
... Gerten, M; + view all
(2020)
Genetic Improvement @ ICSE 2020.
In:
ACM SIGSOFT Software Engineering Notes.
(pp. pp. 24-30).
ACM
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Pageau, C;
Blot, A;
Hoos, HH;
Kessaci, ME;
Jourdan, L;
(2019)
Configuration of a dynamic MOLS algorithm for Bi-objective flowshop scheduling.
In: Deb, K and Goodman, E and Coello Coello, CA and Klamroth, K and Miettinen, K and Mostaghim, S and Reed, P, (eds.)
Evolutionary Multi-Criterion Optimization: 10th International Conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019, Proceedings.
(pp. pp. 565-577).
Springer: Cham, Switzerland.
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Petke, J;
Blot, A;
(2020)
Refining Fitness Functions in Test-Based Program Repair.
In:
ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops.
(pp. pp. 13-14).
ACM
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Smigielska, M;
Blot, A;
Petke, J;
(2021)
Empirical Analysis of Mutation Operator Selection Strategies for Genetic Improvement.
In:
2021 IEEE/ACM International Workshop on Genetic Improvement (GI).
IEEE
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Zuo, Shengjie;
Blot, Aymeric;
Petke, Justyna;
(2022)
Evaluation of genetic improvement tools for improvement of non-functional properties of software.
In:
GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference CompanionProceedings of the Genetic and Evolutionary Computation Conference Companion.
(pp. pp. 1956-1965).
Association for Computing Machinery (ACM): New York, NY, USA.
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Working / discussion paper
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Blot, Aymeric;
Petke, Justyna;
(2022)
MAGPIE: Machine Automated General Performance Improvement via Evolution of Software.
ArXiv
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