Multi-objective multi-fidelity optimization with ordinal transformation and optimal sampling

Haobin Li, Yueqi Li, Loo Hay Lee, Ek Peng Chew, Giulia Pedrielli, Chun Hung Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

In simulation-optimization, the accurate evaluation of candidate solutions can be obtained by running a high-fidelity model, which is fully featured but time-consuming. Less expensive and lower fidelity models can be particularly useful in simulation-optimization settings. However, the procedure has to account for the inaccuracy of the low fidelity model. Xu et al. (2015) proposed the MO2TOS, a Multi-fidelity Optimization (MO) algorithm, which introduces the concept of ordinal transformation (OT) and uses optimal sampling (OS) to exploit models of multiple fidelities for efficient optimization. In this paper, we propose MO-MO2TOS for the multi-objective case using the concepts of non-dominated sorting and crowding distance to perform OT and OS in this setting. Numerical experiments show the satisfactory performance of the procedure while analyzing the behavior of MO-MO2TOS under different consistency scenarios of the low-fidelity model. This analysis provides insights on future studies in this area.

Original languageEnglish (US)
Title of host publication2015 Winter Simulation Conference, WSC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3737-3748
Number of pages12
Volume2016-February
ISBN (Electronic)9781467397438
DOIs
StatePublished - Feb 16 2016
Externally publishedYes
EventWinter Simulation Conference, WSC 2015 - Huntington Beach, United States
Duration: Dec 6 2015Dec 9 2015

Other

OtherWinter Simulation Conference, WSC 2015
CountryUnited States
CityHuntington Beach
Period12/6/1512/9/15

Fingerprint

Fidelity
Sampling
Optimization
Simulation Optimization
Sorting
Model
Optimization Algorithm
Numerical Experiment
Scenarios
Evaluation
Experiments

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

Cite this

Li, H., Li, Y., Lee, L. H., Chew, E. P., Pedrielli, G., & Chen, C. H. (2016). Multi-objective multi-fidelity optimization with ordinal transformation and optimal sampling. In 2015 Winter Simulation Conference, WSC 2015 (Vol. 2016-February, pp. 3737-3748). [7408531] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSC.2015.7408531

Multi-objective multi-fidelity optimization with ordinal transformation and optimal sampling. / Li, Haobin; Li, Yueqi; Lee, Loo Hay; Chew, Ek Peng; Pedrielli, Giulia; Chen, Chun Hung.

2015 Winter Simulation Conference, WSC 2015. Vol. 2016-February Institute of Electrical and Electronics Engineers Inc., 2016. p. 3737-3748 7408531.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Li, H, Li, Y, Lee, LH, Chew, EP, Pedrielli, G & Chen, CH 2016, Multi-objective multi-fidelity optimization with ordinal transformation and optimal sampling. in 2015 Winter Simulation Conference, WSC 2015. vol. 2016-February, 7408531, Institute of Electrical and Electronics Engineers Inc., pp. 3737-3748, Winter Simulation Conference, WSC 2015, Huntington Beach, United States, 12/6/15. https://doi.org/10.1109/WSC.2015.7408531
Li H, Li Y, Lee LH, Chew EP, Pedrielli G, Chen CH. Multi-objective multi-fidelity optimization with ordinal transformation and optimal sampling. In 2015 Winter Simulation Conference, WSC 2015. Vol. 2016-February. Institute of Electrical and Electronics Engineers Inc. 2016. p. 3737-3748. 7408531 https://doi.org/10.1109/WSC.2015.7408531
Li, Haobin ; Li, Yueqi ; Lee, Loo Hay ; Chew, Ek Peng ; Pedrielli, Giulia ; Chen, Chun Hung. / Multi-objective multi-fidelity optimization with ordinal transformation and optimal sampling. 2015 Winter Simulation Conference, WSC 2015. Vol. 2016-February Institute of Electrical and Electronics Engineers Inc., 2016. pp. 3737-3748
@inproceedings{82a48bf3901647229c21a4bc76c7bae7,
title = "Multi-objective multi-fidelity optimization with ordinal transformation and optimal sampling",
abstract = "In simulation-optimization, the accurate evaluation of candidate solutions can be obtained by running a high-fidelity model, which is fully featured but time-consuming. Less expensive and lower fidelity models can be particularly useful in simulation-optimization settings. However, the procedure has to account for the inaccuracy of the low fidelity model. Xu et al. (2015) proposed the MO2TOS, a Multi-fidelity Optimization (MO) algorithm, which introduces the concept of ordinal transformation (OT) and uses optimal sampling (OS) to exploit models of multiple fidelities for efficient optimization. In this paper, we propose MO-MO2TOS for the multi-objective case using the concepts of non-dominated sorting and crowding distance to perform OT and OS in this setting. Numerical experiments show the satisfactory performance of the procedure while analyzing the behavior of MO-MO2TOS under different consistency scenarios of the low-fidelity model. This analysis provides insights on future studies in this area.",
author = "Haobin Li and Yueqi Li and Lee, {Loo Hay} and Chew, {Ek Peng} and Giulia Pedrielli and Chen, {Chun Hung}",
year = "2016",
month = "2",
day = "16",
doi = "10.1109/WSC.2015.7408531",
language = "English (US)",
volume = "2016-February",
pages = "3737--3748",
booktitle = "2015 Winter Simulation Conference, WSC 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",

}

TY - GEN

T1 - Multi-objective multi-fidelity optimization with ordinal transformation and optimal sampling

AU - Li, Haobin

AU - Li, Yueqi

AU - Lee, Loo Hay

AU - Chew, Ek Peng

AU - Pedrielli, Giulia

AU - Chen, Chun Hung

PY - 2016/2/16

Y1 - 2016/2/16

N2 - In simulation-optimization, the accurate evaluation of candidate solutions can be obtained by running a high-fidelity model, which is fully featured but time-consuming. Less expensive and lower fidelity models can be particularly useful in simulation-optimization settings. However, the procedure has to account for the inaccuracy of the low fidelity model. Xu et al. (2015) proposed the MO2TOS, a Multi-fidelity Optimization (MO) algorithm, which introduces the concept of ordinal transformation (OT) and uses optimal sampling (OS) to exploit models of multiple fidelities for efficient optimization. In this paper, we propose MO-MO2TOS for the multi-objective case using the concepts of non-dominated sorting and crowding distance to perform OT and OS in this setting. Numerical experiments show the satisfactory performance of the procedure while analyzing the behavior of MO-MO2TOS under different consistency scenarios of the low-fidelity model. This analysis provides insights on future studies in this area.

AB - In simulation-optimization, the accurate evaluation of candidate solutions can be obtained by running a high-fidelity model, which is fully featured but time-consuming. Less expensive and lower fidelity models can be particularly useful in simulation-optimization settings. However, the procedure has to account for the inaccuracy of the low fidelity model. Xu et al. (2015) proposed the MO2TOS, a Multi-fidelity Optimization (MO) algorithm, which introduces the concept of ordinal transformation (OT) and uses optimal sampling (OS) to exploit models of multiple fidelities for efficient optimization. In this paper, we propose MO-MO2TOS for the multi-objective case using the concepts of non-dominated sorting and crowding distance to perform OT and OS in this setting. Numerical experiments show the satisfactory performance of the procedure while analyzing the behavior of MO-MO2TOS under different consistency scenarios of the low-fidelity model. This analysis provides insights on future studies in this area.

UR - http://www.scopus.com/inward/record.url?scp=84962909254&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84962909254&partnerID=8YFLogxK

U2 - 10.1109/WSC.2015.7408531

DO - 10.1109/WSC.2015.7408531

M3 - Conference contribution

AN - SCOPUS:84962909254

VL - 2016-February

SP - 3737

EP - 3748

BT - 2015 Winter Simulation Conference, WSC 2015

PB - Institute of Electrical and Electronics Engineers Inc.

ER -