2021
DOI: 10.1007/978-3-030-76020-5_4
|View full text |Cite
|
Sign up to set email alerts
|

Product Optimization in Stepwise Design

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
1
0

Year Published

2022
2022
2023
2023

Publication Types

Select...
3
1

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(4 citation statements)
references
References 28 publications
0
1
0
Order By: Relevance
“…Inferring these values (that is, building a performance model) is a research direction by itself [21], and an accurate performance model can help to significantly improve the performance of a given optimisation framework [43]. As an alternative to building a performance model, it has been proposed [44], [45] to use random sampling to directly infer configurations, and optimise them by identifying features contributing to improved performance. This solution offers performance benefits when the attribute values are unknown.…”
Section: Related Workmentioning
confidence: 99%
“…Inferring these values (that is, building a performance model) is a research direction by itself [21], and an accurate performance model can help to significantly improve the performance of a given optimisation framework [43]. As an alternative to building a performance model, it has been proposed [44], [45] to use random sampling to directly infer configurations, and optimise them by identifying features contributing to improved performance. This solution offers performance benefits when the attribute values are unknown.…”
Section: Related Workmentioning
confidence: 99%
“…uniform random sampling (URS) (Heradio et al, 2022a). URS is the simplest way to solve search-related problems on configurable systems (Oh et al, 2017;Heradio et al, 2022b;Batory et al, 2021). URS-based search consists of generating a random sample of configurations, testing (or benchmarking) them, and selecting the ones that fail (or the one that achieves the best performance).…”
Section: Lessons Learned and Open Challengesmentioning
confidence: 99%
“…LS7 Uniform random sampling may improve the performance of Monte Carlo simulations. A possible solution to address the previous challenge is to replace the actions (Section 5) for selecting the features individually with uniform random sampling (Heradio et al, 2022a;Batory et al, 2021;Oh et al, 2017), which returns a sample of configurations of size equal to the number of simulations needed. We can substitute the random choices during the simulation step of the MCTS method by a random sample representing the terminal states reached by the simulations.…”
Section: Lessons Learned and Open Challengesmentioning
confidence: 99%
See 1 more Smart Citation