Search Results - Parameter tuning and algorithm configuration

Using Latin Hypercube Hammersley Sampling Method for Algorithm Parameter Tuning: A Case for Differential Ant-Stigmergy Algorithm.

Authors: Eryoldaş, Yasemin Durmuşoğlu, Alptekin

Source: IEOM Annual International Conference Proceedings; Mar2021, p2975-2982, 8p

Subject Terms: HYPERCUBE networks (Computer networks), HEURISTIC algorithms, ALGORITHMS, PRODUCTION control, LEAN management

An investigation of factors influencing algorithm selection for high dimensional continuous optimisation problems

Authors: Graham, Kevin Brownlee, Alexander Cairns, David et al.

Contributors: Graham, Kevin Brownlee, Alexander Cairns, David et al.

Subject Terms: 519.6, large-scale optimisation, metaheuristics, algorithm selection, automatic parameter tuning, parameter tuning, algorithm configuration, continuous optimisation, optimisation, optimization, optimisation benchmark, genetic algorithm, particle swarm optimisation, differential evolution, covarience matrix adaptation evolutionary strategy, simulated annealing, hill climbing, search-based optimisation, metaheuristic search, metaheuristic scalability, Algorithm, Simulated annealing (Mathematics)

Access URL: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.800945

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

Characteristic feature analysis of continuous optimization problems based on Variability Map of objective function for optimization algorithm configuration

Authors: Agasiev Taleh

Source: Open Computer Science, Vol 10, Iss 1, Pp 97-111 (2020)

Subject Terms: global optimization, continuous optimization problem, meta-optimization, algorithm configuration, parameter tuning, dependency decomposition approach, characteristic features, exploratory landscape analysis, variability map, generalized information content, sectorization method, Electronic computers. Computer science, QA75.5-76.95

File Description: electronic resource

Relation: http://www.degruyter.com/view/j/comp.2020.10.issue-1/comp-2020-0114/comp-2020-0114.xml?format=INT; https://doaj.org/toc/2299-1093

Access URL: https://doaj.org/article/15e585c962fe480c928f303ba57ead45

Comparison of Tree‐Based Machine Learning Algorithms for Classification of Livestock Breeds Based On Post‐Thaw Spermatological Parameters.

Authors: Özen, Doğukan Özen, Hülya Gül, Elif Bersu et al.

Source: Veterinary Medicine & Science. Sep2025, Vol. 11 Issue 5, p1-10. 10p.

Subjects: Livestock breeds, Machine learning, Semen analysis, CART algorithms, Classification, Cattle breeds

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

Performance Assessment of Metaheuristic Algorithms for Structural Optimization Taking Into Account the Influence of Algorithmic Control Parameters

Authors: Wouter Dillen Geert Lombaert Mattias Schevenels

Source: Frontiers in Built Environment, Vol 7 (2021)

Subject Terms: stochastic optimization, genetic algorithm, statistical analysis, parameter tuning, algorithm configuration, hyperparameter optimization, Engineering (General). Civil engineering (General), TA1-2040, City planning, HT165.5-169.9

File Description: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fbuil.2021.618851/full; https://doaj.org/toc/2297-3362

Access URL: https://doaj.org/article/519a6981f8334e588bb66f05afda6098

ACVIZ: A tool for the visual analysis of the configuration of algorithms with irace

Authors: Marcelo de Souza Marcus Ritt Manuel López-Ibáñez et al.

Source: Operations Research Perspectives, Vol 8, Iss , Pp 100186- (2021)

Subject Terms: Algorithm configuration, Parameter tuning, irace, Mathematics, QA1-939

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2214716021000099; https://doaj.org/toc/2214-7160

Access URL: https://doaj.org/article/87702e53e3ed4647ab71e2e062b50694

A Literature Survey on Offline Automatic Algorithm Configuration

Authors: Yasemin Eryoldaş Alptekin Durmuşoglu

Source: Applied Sciences, Vol 12, Iss 13, p 6316 (2022)

Subject Terms: metaheuristics, offline algorithm configuration, parameter tuning, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

File Description: electronic resource

Relation: https://www.mdpi.com/2076-3417/12/13/6316; https://doaj.org/toc/2076-3417

Access URL: https://doaj.org/article/dc825d69dd2446fe80c83aa7a3f63efc

The multi-objective instance-specific algorithm configuration problem: a case study on genetic algorithms solving the vehicle routing problem

Authors: Hocke, Stephan

Thesis Advisors: Schönberger, Jörn, Neufeld, Janis Sebastian, Technische Universität Dresden

Subject Terms: parameter configuration, parameter tuning, bayesian optimization, vehicle routing problem, genetic algorithm, info:eu-repo/classification/ddc/320, ddc:320, info:eu-repo/classification/ddc/004, ddc:004

Availability: https://tud.qucosa.de/id/qucosa%3A93745
https://tud.qucosa.de/api/qucosa%3A93745/attachment/ATT-0/

Dynamic instance sampling for multi-objective automatic algorithm configuration.

Authors: Li, Yuchen Wang, Handing

Source: Swarm & Evolutionary Computation. Aug2025, Vol. 97, pN.PAG-N.PAG. 1p.

Subject Terms: Multi-objective optimization, Budget, Kriging, Algorithms, Cost

The irace package: Iterated racing for automatic algorithm configuration

Authors: Manuel López-Ibáñez Jérémie Dubois-Lacoste Leslie Pérez Cáceres et al.

Source: Operations Research Perspectives, Vol 3, Iss C, Pp 43-58 (2016)

Subject Terms: Automatic algorithm configuration, Racing, Parameter tuning, Mathematics, QA1-939

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2214716015300270; https://doaj.org/toc/2214-7160

Access URL: https://doaj.org/article/36bc1e6a0c7645afb2917fd3a325a6f7

How Much Data Is Sufficient to Learn High-Performing Algorithms?

Authors: Balcan, Maria-Florina Deblasio, Dan Dick, Travis et al.

Source: Journal of the ACM. Oct2024, Vol. 71 Issue 5, p1-58. 58p.

Subject Terms: *MACHINE theory, CLUSTERING algorithms, GREEDY algorithms, MACHINE learning, COMPUTATIONAL biology

Towards Automatic Generation of Performance Models for Dynamic Tuning using Machine Learning

Authors: Alcaraz Rodriguez, Jordi

Thesis Advisors: jordi_alc@hotmail.com, Sikora, Anna, César Galobardes, Eduardo

Source: TDX (Tesis Doctorals en Xarxa)

Subject Terms: Aprenentatge automàtic, Aprendizaje automático, Machine learning, Eines de rendiment, Herramientas de rendimiento, Performance tools, Computació d'altes prestacions, Computación de altas prestaciones, High performance computing, Ciències Experimentals

File Description: application/pdf

Access URL: http://hdl.handle.net/10803/675104

Automatic parameter tuning in localization algorithms

Automatisk parameterjustering av lokaliseringsalgoritmer

Authors: Lundberg, Martin

Subject Terms: cma-es, covariance matrix adaptation, evolution strategies, bayesian optimization, black box optimization, object localization, 3d localization, bin picking, parameter tuning, algorithm configuration, Computer and Information Sciences, Data- och informationsvetenskap

File Description: application/pdf

Availability: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-158132

A Bayesian Optimization Approach for Tuning a Grouping Genetic Algorithm for Solving Practically Oriented Pickup and Delivery Problems

Authors: Cornelius Rüther Julia Rieck

Source: Logistics, Vol 8, Iss 1, p 14 (2024)

Subject Terms: automatic algorithm configuration, black box optimization, Gaussian processes, machine learning model, Transportation and communication, K4011-4343, Management. Industrial management, HD28-70, Transportation and communications, HE1-9990

File Description: electronic resource

Relation: https://www.mdpi.com/2305-6290/8/1/14; https://doaj.org/toc/2305-6290

Access URL: https://doaj.org/article/980c5c09cb394228a647ff779b0863d1

An efficient parameter tuning method based on the Latin Hypercube Hammersley Sampling and fuzzy C-Means clustering methods.

Authors: Eryoldaş, Yasemin Durmuşoğlu, Alptekin

Source: Journal of King Saud University - Computer & Information Sciences. Nov2022:Part A, Vol. 34 Issue 10, p8307-8322. 16p.

Subject Terms: Latin hypercube sampling, Genetic algorithms, Metaheuristic algorithms

Parameter tuning for cross-domain search

Authors: Gumus, Duriye Betul

Subject Terms: 006.3, QA 75 Electronic computers. Computer science

Access URL: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.813180

Body Weight Estimation in Holstein × Zebu Crossbred Heifers: Comparative Analysis of XGBoost and LightGBM Algorithms.

Authors: Herrera‐Camacho, Jose Tırınk, Cem Parra‐Cortés, Rosa Inés et al.

Source: Veterinary Medicine & Science. Jul2025, Vol. 11 Issue 4, p1-10. 10p.

Subjects: Machine learning, Milk yield, Body weight, Heifers, Rural geography

Comparison of sampling methods for algorithm configuration problem: A case for tuning differential ant-stigmergy (DASA) algorithm parameters.

Authors: Eryoldaş, Yasemin Durmuşoğlu, Alptekin

Source: Computers & Industrial Engineering. Jun2021, Vol. 156, pN.PAG-N.PAG. 1p.

Subject Terms: *HEURISTIC, *ALGORITHMS, SAMPLING methods, LATIN hypercube sampling