Data-Driven Multi-Objective Optimization: Analysis of Current Methods and Techniques

Ernesto Pereiras; Yamisleydi Salgueiro; Gonzalo Nápoles; Marco Rivera

doi:10.1109/CHILECON60335.2023.10418625

Data-Driven Multi-Objective Optimization: Analysis of Current Methods and Techniques

Ernesto Pereiras, Yamisleydi Salgueiro, Gonzalo Nápoles, Marco Rivera

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Original language	English
Title of host publication	2023 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)
Pages	1-6
Number of pages	6
DOIs	https://doi.org/10.1109/CHILECON60335.2023.10418625
Publication status	Published - 2023

Keywords

Measurement
Analytical models
Machine learning algorithms
Optimization methods
Focusing
Machine learning
Information and communication technology
data-driven algorithms
interpretability
machine learning
multi-objective optimization
surrogate model

Access to Document

10.1109/CHILECON60335.2023.10418625

Cite this

@inproceedings{6a66e541d55344519918eb1e35782154,

title = "Data-Driven Multi-Objective Optimization: Analysis of Current Methods and Techniques",

keywords = "Measurement, Analytical models, Machine learning algorithms, Optimization methods, Focusing, Machine learning, Information and communication technology, data-driven algorithms, interpretability, machine learning, multi-objective optimization, surrogate model",

author = "Ernesto Pereiras and Yamisleydi Salgueiro and Gonzalo N{\'a}poles and Marco Rivera",

year = "2023",

doi = "10.1109/CHILECON60335.2023.10418625",

language = "English",

pages = "1--6",

booktitle = "2023 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)",

}

Data-Driven Multi-Objective Optimization: Analysis of Current Methods and Techniques. / Pereiras, Ernesto; Salgueiro, Yamisleydi; Nápoles, Gonzalo et al.
2023 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON). 2023. p. 1-6.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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T1 - Data-Driven Multi-Objective Optimization: Analysis of Current Methods and Techniques

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AU - Nápoles, Gonzalo

AU - Rivera, Marco

PY - 2023

Y1 - 2023

KW - Measurement

KW - Analytical models

KW - Machine learning algorithms

KW - Optimization methods

KW - Focusing

KW - Machine learning

KW - Information and communication technology

KW - data-driven algorithms

KW - interpretability

KW - machine learning

KW - multi-objective optimization

KW - surrogate model

U2 - 10.1109/CHILECON60335.2023.10418625

DO - 10.1109/CHILECON60335.2023.10418625

M3 - Conference contribution

SP - 1

EP - 6

BT - 2023 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)

ER -