Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Sara Tari"'
Publikováno v:
Natural Computing
Natural Computing, Springer Verlag, 2020, ⟨10.1007/s11047-020-09822-2⟩
Natural Computing, Springer Verlag, 2020, ⟨10.1007/s11047-020-09822-2⟩
A major issue while conceiving or parameterizing an optimization heuristic is to ensure an appropriate balance between exploitation and exploration of the search. Evolution strategies and neighborhood-based metaheuristics constitute relevant high-lev
Autor:
Gabriela Ochoa, Sara Tari
Publikováno v:
GECCO
GECCO '21: Genetic and Evolutionary Computation Conference
GECCO '21: Genetic and Evolutionary Computation Conference, Jul 2021, Lille France, France. pp.278-286, ⟨10.1145/3449639.3459295⟩
GECCO '21: Genetic and Evolutionary Computation Conference
GECCO '21: Genetic and Evolutionary Computation Conference, Jul 2021, Lille France, France. pp.278-286, ⟨10.1145/3449639.3459295⟩
In local search algorithms, the pivoting rule determines which neighboring solution to select and thus strongly influences the behavior of the algorithm and its capacity to sample good-quality local optima. The classical pivoting rules are first and
Publikováno v:
International Transactions in Operational Research
International Transactions in Operational Research, Wiley, 2021, ⟨10.1111/itor.12983⟩
International Transactions in Operational Research, Wiley, 2021, ⟨10.1111/itor.12983⟩
International audience
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9810b1bdc4c4a4c5ae7e574fb4e16c71
https://hal.archives-ouvertes.fr/hal-03384306
https://hal.archives-ouvertes.fr/hal-03384306
Publikováno v:
Parallel Problem Solving from Nature – PPSN XVI. PPSN 2020
PPSN 2020
PPSN 2020, Sep 2020, Leiden, Netherlands. pp.65-77, ⟨10.1007/978-3-030-58112-1_5⟩
Parallel Problem Solving from Nature – PPSN XVI ISBN: 9783030581114
PPSN (1)
PPSN 2020
PPSN 2020, Sep 2020, Leiden, Netherlands. pp.65-77, ⟨10.1007/978-3-030-58112-1_5⟩
Parallel Problem Solving from Nature – PPSN XVI ISBN: 9783030581114
PPSN (1)
MOCA-I is a multi-objective local search algorithm, based on the Pittsburgh representation, that has been formerly designed to solve partial classification problems with imbalanced data. Recently, multi-objective automatic algorithm configuration (MO
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f5145b5ffa418ae2c54fc1baf0ca08bd
https://hal.science/hal-02932462
https://hal.science/hal-02932462
Autor:
Marie-Eléonore Kessaci, Laetitia Jourdan, Nicolas Szczepanski, Lucien Mousin, Sara Tari, Julie Jacques
Publikováno v:
2020 IEEE Congress on Evolutionary Computation (CEC)
2020 IEEE Congress on Evolutionary Computation (CEC), Jul 2020, Glasgow, United Kingdom. pp.1-8, ⟨10.1109/CEC48606.2020.9185785⟩
CEC
2020 IEEE Congress on Evolutionary Computation (CEC), Jul 2020, Glasgow, United Kingdom. pp.1-8, ⟨10.1109/CEC48606.2020.9185785⟩
CEC
Classification problems can be modeled as multi-objective optimization problems. MOCA-I is a multi-objective local search designed to solve these problems, particularly when the data are imbalanced. However, this algorithm has been tuned by hand in o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5fd7c30ca623b9192fc012407407d3f
https://hal.science/hal-02935096
https://hal.science/hal-02935096
Publikováno v:
Congrès annuel de la société Française de Recherche Opérationnelle et d’Aide à la Décision (ROADEF)
Congrès annuel de la société Française de Recherche Opérationnelle et d’Aide à la Décision (ROADEF), Feb 2020, Montpellier, France
HAL
Congrès annuel de la société Française de Recherche Opérationnelle et d’Aide à la Décision (ROADEF), Feb 2020, Montpellier, France
HAL
International audience
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::c933d4999f107966a2c8fc6b99e990c9
https://hal.archives-ouvertes.fr/hal-02875059
https://hal.archives-ouvertes.fr/hal-02875059
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030535513
LION
LION 2020-Learning and Intelligent Optimization
LION 2020-Learning and Intelligent Optimization, 2020, Athens, Greece. pp.151-157, ⟨10.1007/978-3-030-53552-0_16⟩
LION
LION 2020-Learning and Intelligent Optimization
LION 2020-Learning and Intelligent Optimization, 2020, Athens, Greece. pp.151-157, ⟨10.1007/978-3-030-53552-0_16⟩
International audience; Volatile organic compounds (VOCs) are continuous medical data regularly studied to perform non-invasive diagnosis of diseases using machine learning tasks for example. The project PATHACOV aims to use VOCs in order to predict
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e99c05758f5144d380b7206039e5ecb7
https://doi.org/10.1007/978-3-030-53552-0_16
https://doi.org/10.1007/978-3-030-53552-0_16
Publikováno v:
Operations Research/Computer Science Interfaces Series ISBN: 9783319582528
Recent Developments of Metaheuristics
Recent Developments of Metaheuristics, 2018
Recent Developments of Metaheuristics
Recent Developments of Metaheuristics, 2018
Many combinatorial optimization problem solvers are based on stochastic local search algorithms, which mainly differ by their move selection strategies, also called pivoting rules. In this chapter, we aim at determining pivoting rules that allow hill
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::72f1f58d746a5683cdc6fb0f25e67fcb
https://doi.org/10.1007/978-3-319-58253-5_7
https://doi.org/10.1007/978-3-319-58253-5_7
Publikováno v:
International Conference on Artificial Evolution (EA)
International Conference on Artificial Evolution (EA), 2017, Paris, France. pp.53-64
Lecture Notes in Computer Science ISBN: 9783319781327
Artificial Evolution
International Conference on Artificial Evolution (EA), 2017, Paris, France. pp.53-64
Lecture Notes in Computer Science ISBN: 9783319781327
Artificial Evolution
In this paper we present and investigate partial neighborhood local searches, which only explore a sample of the neighborhood at each step of the search. We particularly focus on establishing link between the structure of optimization problems and th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fce02f269337953cf3e3516f0d034cde
https://hal.univ-angers.fr/hal-02715062
https://hal.univ-angers.fr/hal-02715062
Publikováno v:
GECCO (Companion)
Despite the huge number of studies in the metaheuristic field, it remains difficult to understand the relative impact of their elementary components. A major aspect determining the general efficiency of metaheuristics resides in the way to exploit a