V-Shaped sampling based on kendall-distance to enhance optimization with ranks

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

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

1 Citation (Scopus)

Abstract

In the area of discrete optimization via simulation (DOvS), optimization over rank values has been of concern in computer science and, more recently, in multi-fidelity simulation optimization. Specifically, Chen et al. (2015) proposes the concept of Ordinal Transformation to translate multi-dimensional discrete optimization problems into single-dimensional problems which are simpler, and the transformed solution space is referred as ordinal space. In this paper, we build on the idea of ordinal transformation and its properties in order to derive an efficient sampling algorithm for identifying the solution with the best rank in the setting of multi-fidelity optimization. We refer to this algorithm as V-shaped and we use the concept of Kendall distance adopted in the machine learning theory, in order to characterize solutions in the OT space. The algorithm is presented for the first time and preliminary performance results are provided comparing the algorithm with the sampling proposed in Chen et al. (2015).

Original languageEnglish (US)
Title of host publication2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages671-681
Number of pages11
ISBN (Electronic)9781509044863
DOIs
StatePublished - Jan 17 2017
Externally publishedYes
Event2016 Winter Simulation Conference, WSC 2016 - Arlington, United States
Duration: Dec 11 2016Dec 14 2016

Other

Other2016 Winter Simulation Conference, WSC 2016
CountryUnited States
CityArlington
Period12/11/1612/14/16

Fingerprint

Sampling
Simulation Optimization
Optimization
Discrete Optimization
Fidelity
Learning Theory
Machine Learning
Computer Science
Computer science
Learning systems
Optimization Problem
Concepts

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

Cite this

Li, H., Pedrielli, G., Chen, M., Lee, L. H., Chew, E. P., & Chen, C. H. (2017). V-Shaped sampling based on kendall-distance to enhance optimization with ranks. In 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016 (pp. 671-681). [7822131] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSC.2016.7822131

V-Shaped sampling based on kendall-distance to enhance optimization with ranks. / Li, Haobin; Pedrielli, Giulia; Chen, Min; Lee, Loo Hay; Chew, Ek Peng; Chen, Chun Hung.

2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 671-681 7822131.

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

Li, H, Pedrielli, G, Chen, M, Lee, LH, Chew, EP & Chen, CH 2017, V-Shaped sampling based on kendall-distance to enhance optimization with ranks. in 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016., 7822131, Institute of Electrical and Electronics Engineers Inc., pp. 671-681, 2016 Winter Simulation Conference, WSC 2016, Arlington, United States, 12/11/16. https://doi.org/10.1109/WSC.2016.7822131
Li H, Pedrielli G, Chen M, Lee LH, Chew EP, Chen CH. V-Shaped sampling based on kendall-distance to enhance optimization with ranks. In 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 671-681. 7822131 https://doi.org/10.1109/WSC.2016.7822131
Li, Haobin ; Pedrielli, Giulia ; Chen, Min ; Lee, Loo Hay ; Chew, Ek Peng ; Chen, Chun Hung. / V-Shaped sampling based on kendall-distance to enhance optimization with ranks. 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 671-681
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