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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.00727 |
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| _version_ | 1866910036646690816 |
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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 |