A Test Points Selection Strategy Based on the Improved Binary Particle Swarm-genetic Algorithm

Yuhang Liu; Zhiming Yang; Yang Yu; Yu Peng

doi:10.1109/PHM-Xian66756.2025.11427743

A Test Points Selection Strategy Based on the Improved Binary Particle Swarm-genetic Algorithm

Yuhang Liu^*
, Zhiming Yang
, Yang Yu
, Yu Peng

^*Corresponding author for this work

School of Electronics and Information Engineering, Harbin Institute of Technology
Beijing Aerospace Automatic Control Institute

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

Abstract

Test point optimization, a constrained multi-objective combinatorial optimization problem, is critical for system testability design. This paper proposes an Improved Binary Particle Swarm-Genetic Algorithm (IBPS-GA). Verified via five classic benchmark functions, the algorithm exhibits high reliability, accuracy, and robustness. A case study on the interface converter module of a rocket control system shows that IBPS-GA reduces test points by 50% and test costs by 56.4%, while achieving fault detection and isolation rates exceeding 90% (with the latter doubled), meeting engineering requirement.

Original language	English
Title of host publication	2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025
Editors	Huimin Wang, Steven Li
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798331526757
DOIs	https://doi.org/10.1109/PHM-Xian66756.2025.11427743
State	Published - 2025
Externally published	Yes
Event	16th IEEE Reliability and Prognostics and Health Management Conference, PHM-Xian 2025 - Xian, China Duration: 10 Oct 2025 → 12 Oct 2025

Publication series

Name	2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025

Conference

Conference	16th IEEE Reliability and Prognostics and Health Management Conference, PHM-Xian 2025
Country/Territory	China
City	Xian
Period	10/10/25 → 12/10/25

Keywords

Constrained Multi-Objective Optimization
Improved Binary Particle Swarm-Genetic Algorithm
Test point optimization
Testability Design

Access to Document

10.1109/PHM-Xian66756.2025.11427743

Cite this

Liu, Y., Yang, Z., Yu, Y., & Peng, Y. (2025). A Test Points Selection Strategy Based on the Improved Binary Particle Swarm-genetic Algorithm. In H. Wang, & S. Li (Eds.), 2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025 (2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PHM-Xian66756.2025.11427743

Liu, Yuhang ; Yang, Zhiming ; Yu, Yang et al. / A Test Points Selection Strategy Based on the Improved Binary Particle Swarm-genetic Algorithm. 2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025. editor / Huimin Wang ; Steven Li. Institute of Electrical and Electronics Engineers Inc., 2025. (2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025).

@inproceedings{d64a78a955ec4ff7849344e3aeb713ce,

title = "A Test Points Selection Strategy Based on the Improved Binary Particle Swarm-genetic Algorithm",

abstract = "Test point optimization, a constrained multi-objective combinatorial optimization problem, is critical for system testability design. This paper proposes an Improved Binary Particle Swarm-Genetic Algorithm (IBPS-GA). Verified via five classic benchmark functions, the algorithm exhibits high reliability, accuracy, and robustness. A case study on the interface converter module of a rocket control system shows that IBPS-GA reduces test points by 50\% and test costs by 56.4\%, while achieving fault detection and isolation rates exceeding 90\% (with the latter doubled), meeting engineering requirement.",

keywords = "Constrained Multi-Objective Optimization, Improved Binary Particle Swarm-Genetic Algorithm, Test point optimization, Testability Design",

author = "Yuhang Liu and Zhiming Yang and Yang Yu and Yu Peng",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 16th IEEE Reliability and Prognostics and Health Management Conference, PHM-Xian 2025 ; Conference date: 10-10-2025 Through 12-10-2025",

year = "2025",

doi = "10.1109/PHM-Xian66756.2025.11427743",

language = "英语",

series = "2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

editor = "Huimin Wang and Steven Li",

booktitle = "2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025",

address = "美国",

}

Liu, Y, Yang, Z , Yu, Y & Peng, Y 2025, A Test Points Selection Strategy Based on the Improved Binary Particle Swarm-genetic Algorithm. in H Wang & S Li (eds), 2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025. 2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025, Institute of Electrical and Electronics Engineers Inc., 16th IEEE Reliability and Prognostics and Health Management Conference, PHM-Xian 2025, Xian, China, 10/10/25. https://doi.org/10.1109/PHM-Xian66756.2025.11427743

A Test Points Selection Strategy Based on the Improved Binary Particle Swarm-genetic Algorithm. / Liu, Yuhang; Yang, Zhiming ; Yu, Yang et al.
2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025. ed. / Huimin Wang; Steven Li. Institute of Electrical and Electronics Engineers Inc., 2025. (2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025).

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

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T1 - A Test Points Selection Strategy Based on the Improved Binary Particle Swarm-genetic Algorithm

AU - Liu, Yuhang

AU - Yang, Zhiming

AU - Yu, Yang

AU - Peng, Yu

PY - 2025

Y1 - 2025

N2 - Test point optimization, a constrained multi-objective combinatorial optimization problem, is critical for system testability design. This paper proposes an Improved Binary Particle Swarm-Genetic Algorithm (IBPS-GA). Verified via five classic benchmark functions, the algorithm exhibits high reliability, accuracy, and robustness. A case study on the interface converter module of a rocket control system shows that IBPS-GA reduces test points by 50% and test costs by 56.4%, while achieving fault detection and isolation rates exceeding 90% (with the latter doubled), meeting engineering requirement.

AB - Test point optimization, a constrained multi-objective combinatorial optimization problem, is critical for system testability design. This paper proposes an Improved Binary Particle Swarm-Genetic Algorithm (IBPS-GA). Verified via five classic benchmark functions, the algorithm exhibits high reliability, accuracy, and robustness. A case study on the interface converter module of a rocket control system shows that IBPS-GA reduces test points by 50% and test costs by 56.4%, while achieving fault detection and isolation rates exceeding 90% (with the latter doubled), meeting engineering requirement.

KW - Constrained Multi-Objective Optimization

KW - Improved Binary Particle Swarm-Genetic Algorithm

KW - Test point optimization

KW - Testability Design

UR - https://www.scopus.com/pages/publications/105037311202

U2 - 10.1109/PHM-Xian66756.2025.11427743

DO - 10.1109/PHM-Xian66756.2025.11427743

M3 - 会议稿件

AN - SCOPUS:105037311202

T3 - 2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025

BT - 2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025

A2 - Wang, Huimin

A2 - Li, Steven

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 16th IEEE Reliability and Prognostics and Health Management Conference, PHM-Xian 2025

Y2 - 10 October 2025 through 12 October 2025

ER -

Liu Y, Yang Z , Yu Y, Peng Y. A Test Points Selection Strategy Based on the Improved Binary Particle Swarm-genetic Algorithm. In Wang H, Li S, editors, 2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025. Institute of Electrical and Electronics Engineers Inc. 2025. (2025 Global Reliability and Prognostics and Health Management Conference, PHM-Xian 2025). doi: 10.1109/PHM-Xian66756.2025.11427743

A Test Points Selection Strategy Based on the Improved Binary Particle Swarm-genetic Algorithm

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