Search Results - Per-Instance Algorithm Configuration

Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP

Authors: Seiler, Moritz Vinzent Rook, Jeroen Heins, Jonathan et al.

Source: 2023 IEEE Symposium Series on Computational Intelligence (SSCI). :361-368

Subject Terms: Per-Instance algorithm configuration, 2024 OA procedure, Traveling salesperson problem, Reinforcement learning, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Per-instance algorithm configuration for production planning in a reconfigurable assembly system

Authors: Daniel Guzman Vargas Sidharta Gautama Mehmet Uzunosmanoglu et al.

Source: 2024 IEEE 22nd Mediterranean Electrotechnical Conference (MELECON). :62-67

Per-Instance Algorithm Configuration in Homogeneous Instance Spaces: A Use Case in Reconfigurable Assembly Systems

Authors: Daniel Guzman Vargas Sidharta Gautama Mehmet Uzunosmanoglu et al.

Source: Applied Sciences, Vol 14, Iss 14, p 6035 (2024)
APPLIED SCIENCES-BASEL

Subject Terms: Technology, Technology and Engineering, QH301-705.5, Physics, QC1-999, 02 engineering and technology, Engineering (General). Civil engineering (General), 01 natural sciences, homogeneous instance spaces, integer quadratic programming, Business and Economics, Chemistry, Mathematics and Statistics, per-instance algorithm configuration, 0202 electrical engineering, electronic engineering, information engineering, reconfigurable assembly systems, NORMALITY, TA1-2040, Biology (General), 0101 mathematics, QD1-999

File Description: application/pdf

Access URL: https://doaj.org/article/4f158222f680466480274445a59fb715
https://biblio.ugent.be/publication/01J4KB37PN3W3RA9E84MG8ZTVN
http://hdl.handle.net/1854/LU-01J4KB37PN3W3RA9E84MG8ZTVN
https://biblio.ugent.be/publication/01J4KB37PN3W3RA9E84MG8ZTVN/file/01J8M91J9EF3GSDR81SVWBDAE6
http://doi.org/10.3390/app14146035

Per instance algorithm configuration of CMA-ES with limited budget

Authors: Belkhir, Nacim Dreo, Johann Savéant, Pierre et al.

Contributors: Belkhir, Nacim Dreo, Johann Savéant, Pierre et al.

Source: Proceedings of the Genetic and Evolutionary Computation Conference. :681-688

Subject Terms: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC], 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, CCS CONCEPTS • General and reference → Empirical studies, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], numerical black box optimization, empirical study, fitness landscape analysis, 0202 electrical engineering, electronic engineering, information engineering, Algorithm Configuration, • Theory of computation → Continuous optimization, Bio-inspired optimization, problem features

File Description: application/pdf

Access URL: https://hal.inria.fr/hal-01613753/file/GECCO2017_nacimbelkhir.pdf
https://inria.hal.science/hal-01613753v1
https://dl.acm.org/citation.cfm?id=3071343
https://dl.acm.org/doi/10.1145/3071178.3071343
https://doi.org/10.1145/3071178.3071343
https://hal.inria.fr/hal-01613753/document
https://hal.inria.fr/hal-01613753
https://dblp.uni-trier.de/db/conf/gecco/gecco2017.html#BelkhirDSS17

Per-Instance Algorithm Configuration in Homogeneous Instance Spaces: A Use Case in Reconfigurable Assembly Systems.

Authors: Guzman Vargas, Daniel Gautama, Sidharta Uzunosmanoglu, Mehmet et al.

Source: Applied Sciences (2076-3417); Jul2024, Vol. 14 Issue 14, p6035, 28p

Subject Terms: MARKET volatility, HOMOGENEOUS spaces, CASE-based reasoning, HYDRA (Marine life), QUADRATIC programming

The Algorithm Configuration Problem

Authors: Iommazzo, Gabriele D'Ambrosio, Claudia Frangioni, Antonio et al.

Index Terms: Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Mathematics - Optimization and Control, text

URL: http://arxiv.org/abs/2403.00898

Per-instance algorithm configuration: from meta-learning to multi-objective decomposition ; Configuração de algoritmos baseada em instância: do meta-aprendizado à decomposição multiobjetivo

Authors: Pavelski, Lucas Marcondes Delgado, Myriam Regattieri de Biase da Silva orcid:0000-0002-2791-174X et al.

Contributors: Pavelski, Lucas Marcondes Delgado, Myriam Regattieri de Biase da Silva orcid:0000-0002-2791-174X et al.

Subject Terms: Algoritmos, Otimização matemática, Heurística, Aprendizado de máquinas, Algorítmos genéticos, Otimização combinatória, Algorithms, Mathematical optimization, Heuristic, Machine learning, Genetic algorithms, Combinatorial optimization, CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO, Engenharia Elétrica

File Description: application/pdf

Relation: http://repositorio.utfpr.edu.br/jspui/handle/1/27906

Availability: http://repositorio.utfpr.edu.br/jspui/handle/1/27906

Per Instance Algorithm Configuration for Continuous Black Box Optimization

Paramétrage automatisé d'algorithme par instance pour l'optimisation numérique boite noire

Authors: Belkhir, Nacim

Thesis Advisors: Université Paris-Saclay (ComUE), Schoenauer, Marc

Subject Terms: Apprentissage statistique, Optimisation, Intelligence artificielle, Machine learning, Artificial intelligence, Optimization

Availability: http://www.theses.fr/2017SACLS455/document

SAPIAS concept: towards an independent self-adaptive per-instance algorithm selection for metaheuristics

Authors: Mohamed Amine El Majdouli

Source: Proceedings of the Genetic and Evolutionary Computation Conference Companion. :1474-1477

Subject Terms: 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 14. Life underwater, 02 engineering and technology, 15. Life on land, 7. Clean energy

Access URL: https://dl.acm.org/doi/pdf/10.1145/3319619.3326881
https://dblp.uni-trier.de/db/conf/gecco/gecco2019c.html#Majdouli19

Per-Instance Configuration of the Modularized CMA-ES by Means of Classifier Chains and Exploratory Landscape Analysis

Authors: Prager, R.P. Traumann, H. Wang, H. et al.

Source: 2020 IEEE Symposium Series on Computational Intelligence (SSCI). :996-1003

Subject Terms: 13. Climate action, 0202 electrical engineering, electronic engineering, information engineering, 14. Life underwater, 0102 computer and information sciences, 02 engineering and technology, 15. Life on land, 7. Clean energy, 01 natural sciences

File Description: application/pdf

Access URL: https://dblp.uni-trier.de/db/conf/ssci/ssci2020.html#PragerTWBK20
https://www.wi.uni-muenster.de/de/forschung/publikationen/161940
https://hdl.handle.net/1887/3631973

Metamodel-based dynamic algorithm configuration using artificial neural networks.

Authors: Dunke, Fabian Nickel, Stefan

Source: International Journal of General Systems; Jan2024, Vol. 53 Issue 1, p41-71, 31p

Subject Terms: METAHEURISTIC algorithms, ALGORITHMS, ARTIFICIAL neural networks, QUALITY of service

Accelerating process control and optimization via machine learning: a review.

Authors: Mitrai, Ilias Daoutidis, Prodromos

Source: Reviews in Chemical Engineering; May2025, Vol. 41 Issue 4, p401-418, 18p

Subject Terms: MACHINE learning, OPTIMIZATION algorithms, MATHEMATICAL optimization, PROCESS control systems, AUTOMATION, STATISTICAL decision making, CHEMICAL engineering

A Literature Survey on Offline Automatic Algorithm Configuration.

Authors: Eryoldaş, Yasemin Durmuşoglu, Alptekin

Source: Applied Sciences (2076-3417); Jul2022, Vol. 12 Issue 13, pN.PAG-N.PAG, 26p

Subject Terms: ALGORITHMS, HEURISTIC, METAHEURISTIC algorithms, ONLINE algorithms, LITERATURE, RESEARCH & development

Characterising fitness landscapes with fitness-probability cloud and its applications to algorithm configuration

Authors: Lu, Guanzhou

Subject Terms: 004, QA75 Electronic computers. Computer science

Access URL: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.589683

Automated Algorithm Selection: Survey and Perspectives

Authors: Kerschke, P. Hoos, H.H. Neumann, F. et al.

Source: Evolutionary Computation. 27:3-45

Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Artificial Intelligence, data streams, Information Storage and Retrieval, Machine Learning (stat.ML), 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, Decision Support Techniques, Pattern Recognition, Automated, Machine Learning (cs.LG), Statistics - Machine Learning, feature-based approaches, Surveys and Questionnaires, metalearning, 0202 electrical engineering, electronic engineering, information engineering, Automated algorithm selection, Humans, Computer Simulation, exploratory landscape analysis, 4. Education, automated algorithm configuration, 16. Peace & justice, combinatorial optimisation, machine learning, Artificial Intelligence (cs.AI), continuous optimisation, Algorithms

Access URL: http://arxiv.org/pdf/1811.11597
https://pubmed.ncbi.nlm.nih.gov/30475672
http://arxiv.org/abs/1811.11597
https://direct.mit.edu/evco/article/27/1/3/1083/Automated-Algorithm-Selection-Survey-and
https://arxiv.org/pdf/1811.11597.pdf
https://www.mitpressjournals.org/doi/full/10.1162/evco_a_00242
https://ieeexplore.ieee.org/abstract/document/8660744
https://europepmc.org/article/MED/30475672
https://dl.acm.org/doi/10.1162/evco_a_00242

A Literature Survey on Instance Specific Algorithm Configuration Methods.

Authors: Eryoldaş, Yasemin Durmuşoğlu, Alptekin

Source: Proceedings of the International Conference on Industrial Engineering & Operations Management; 3/7/2021, p2983-2990, 8p

Subject Terms: ALGORITHMS, INDUSTRIAL engineering, ARTIFICIAL intelligence, PRODUCTION planning, METAHEURISTIC algorithms

Per Instance Algorithm Configuration for Continuous Black Box Optimization ; Paramétrage automatisé d'algorithme par instance pour l'optimisation numérique boite noire

Authors: Belkhir, Nacim Centre Inria de Saclay Institut National de Recherche en Informatique et en Automatique (Inria) et al.

Contributors: Belkhir, Nacim Centre Inria de Saclay Institut National de Recherche en Informatique et en Automatique (Inria) et al.

Source: https://inria.hal.science/tel-01669527 ; Artificial Intelligence [cs.AI]. Université Paris Saclay (COmUE), 2017. English. ⟨NNT : 2017SACLS455⟩.

Subject Terms: Optimization, Artificial intelligence, Machine learning, Apprentissage statistique, Optimisation, Intelligence artificielle, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-RO]Computer Science [cs]/Operations Research [math.OC], [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]

Relation: NNT: 2017SACLS455

Availability: https://inria.hal.science/tel-01669527
https://inria.hal.science/tel-01669527v2/document
https://inria.hal.science/tel-01669527v2/file/75926_BELKHIR_2017_diffusion.pdf

Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach

Authors: El Mesaoudi-Paul, Adil Weiß, Dimitri Bengs, Viktor et al.

Source: Lecture Notes in Computer Science ISBN: 9783030535513

Access URL: https://rd.springer.com/chapter/10.1007/978-3-030-53552-0_22
https://dblp.uni-trier.de/db/conf/lion/lion2020.html#Mesaoudi-PaulWB20
https://link.springer.com/chapter/10.1007/978-3-030-53552-0_22
https://doi.org/10.1007/978-3-030-53552-0_22
https://pub.uni-bielefeld.de/record/2958263
https://doi.org/10.1007/978-3-030-53552-0_22

An Analysis of Effective Per-instance Tailored GAs for the Permutation Flowshop Scheduling Problem.

Authors: Bacha, Sarra Zohra Ahmed Tayeb, Fatima Benbouzid-Si Benatchba, Karima

Source: Procedia Computer Science. 2023, Vol. 225, p3958-3966. 9p.

Subject Terms: Flow shops, Genetic algorithms, Permutations, Heuristic, Gases

Selecting fast algorithms for the capacitated vehicle routing problem with machine learning techniques.

Authors: Asín‐Achá, Roberto Espinoza, Alexis Goldschmidt, Olivier et al.

Source: Networks; Dec2024, Vol. 84 Issue 4, p465-480, 16p

Subject Terms: VEHICLE routing problem, GENETIC algorithms, COMBINATORIAL optimization, GLOBAL optimization, MACHINE learning