A New Optimization Method for evaluating Sobol’ Sensitivity Indices

This paper presents an optimization method based on a particular polynomial lattice rule with interlaced factor two for estimating sensitivity indices in global sensitivity analysis, focusing on total, first-order and second-order Sobol indices.A comparison with one of the best available methods the Modified Sobol Sequence and component by component construction polynomial lattice rule have been done.Relative errors for key output quantities are analyzed and compared.Our results show that the proposed optimization method consistently outperforms other methods in accurately estimating both first-order and total-order sensitivity indices, especially for parameters with smaller effects.These findings highlight the strengths and limitations of each method, providing guidance for selecting appropriate stochastic sampling strategies in computational sensitivity analysis.

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Publication Details

Journal
Annals of Computer Science and Information Systems
Published
2025-10-15
DOI
https://doi.org/10.15439/2025f4849
Primary Topic
Probabilistic and Robust Engineering Design
Type
article
Field-Weighted Citation Impact
0.00

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article

A New Optimization Method for evaluating Sobol’ Sensitivity Indices

Stoyan Tranev, Fatima Sapundzhi, Slavi Georgiev, Velichka Traneva et al.
Annals of Computer Science and Information Systems
Probabilistic and Robust Engineering Design
article

A New Optimization Method for evaluating Sobol’ Sensitivity Indices

Stoyan Tranev, Fatima Sapundzhi, Slavi Georgiev, Velichka Traneva, Venelin Todorov, Mihai Petrov
article en

Abstract

This paper presents an optimization method based on a particular polynomial lattice rule with interlaced factor two for estimating sensitivity indices in global sensitivity analysis, focusing on total, first-order and second-order Sobol indices.A comparison with one of the best available methods the Modified Sobol Sequence and component by component construction polynomial lattice rule have been done.Relative errors for key output quantities are analyzed and compared.Our results show that the proposed optimization method consistently outperforms other methods in accurately estimating both first-order and total-order sensitivity indices, especially for parameters with smaller effects.These findings highlight the strengths and limitations of each method, providing guidance for selecting appropriate stochastic sampling strategies in computational sensitivity analysis.

Annals of Computer Science and Information SystemsVol. 43
Bulgarian Academy of Sciences (BG), Prof. Assen Zlatarov University (BG), Angel Kanchev University of Ruse (BG)
European Commission, Bulgarian National Science Fund
Openalex Percentile: Top 49%
Probabilistic and Robust Engineering Design
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A New Optimization Method for evaluating Sobol’ Sensitivity Indices — Stoyan Tranev, Fatima Sapundzhi, et al. · Annals of Computer Science and Information Systems (2025) | TGRS Research Map | TGRS