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Main Authors: Hung, Hui-Ju, Lee, Guang-Siang, Lu, Chia-Hsun, Shen, Chih-Ya, Yang, De-Nian
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2603.00727
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author Hung, Hui-Ju
Lee, Guang-Siang
Lu, Chia-Hsun
Shen, Chih-Ya
Yang, De-Nian
author_facet Hung, Hui-Ju
Lee, Guang-Siang
Lu, Chia-Hsun
Shen, Chih-Ya
Yang, De-Nian
contents In hybrid workforce configurations, it is important to decide which employees should work onsite or remotely while ensuring the collaboration benefits against contact-based health risks and skill requirements. In this paper, we formulate the Risk-aware Skill-coverage Hybrid Workforce Configuration (RSHWC) problem on a two-layer social network that balances physical contact risks and social collaboration ties to meet skill requirements. We prove that RSHWC is NP-hard and propose the Guided Risk-aware Iterative Assembling (GRIA) algorithm, a multi-stage algorithm that combines risk-aware workforce construction, skill-preserving workforce refinement, and risk-reducing member replacement. Experiments on four real-world networks show that GRIA consistently outperforms state-of-the-art baselines under various settings.
format Preprint
id arxiv_https___arxiv_org_abs_2603_00727
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Risk-Aware Skill-Coverage Hybrid Workforce Configuration on Social Networks
Hung, Hui-Ju
Lee, Guang-Siang
Lu, Chia-Hsun
Shen, Chih-Ya
Yang, De-Nian
Social and Information Networks
In hybrid workforce configurations, it is important to decide which employees should work onsite or remotely while ensuring the collaboration benefits against contact-based health risks and skill requirements. In this paper, we formulate the Risk-aware Skill-coverage Hybrid Workforce Configuration (RSHWC) problem on a two-layer social network that balances physical contact risks and social collaboration ties to meet skill requirements. We prove that RSHWC is NP-hard and propose the Guided Risk-aware Iterative Assembling (GRIA) algorithm, a multi-stage algorithm that combines risk-aware workforce construction, skill-preserving workforce refinement, and risk-reducing member replacement. Experiments on four real-world networks show that GRIA consistently outperforms state-of-the-art baselines under various settings.
title Risk-Aware Skill-Coverage Hybrid Workforce Configuration on Social Networks
topic Social and Information Networks
url https://arxiv.org/abs/2603.00727