Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/103922
Title: | Optimal assignment of infrastructure construction workers | Authors: | Wang, H Yi, W Liu, Y |
Issue Date: | 2022 | Source: | Electronic research archive, 2022, v. 30, no. 11, p. 4178-4190 | Abstract: | Worker assignment is a classic topic in infrastructure construction. In this study, we developed an integer optimization model to help decision-makers make optimal worker assignment plans while maximizing the daily productivity of all workers. Our proposed model considers the professional skills and physical fitness of workers. Using a real-world dataset, we adopted a machine learning method to estimate the maximum working tolerance time for different workers to carry out different jobs. The real-world dataset also demonstrates the effectiveness of our optimization model. Our work can help project managers achieve efficient management and save labor costs. | Keywords: | Infrastructure management Worker assignment Integer programming Machine learning |
Publisher: | American Institute of Mathematical Sciences | Journal: | Electronic research archive | EISSN: | 2688-1594 | DOI: | 10.3934/era.2022211 | Rights: | ©2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0). The following publication Wang, H., Yi, W., & Liu, Y. (2022). Optimal assignment of infrastructure construction workers. Electronic Research Archive, 30(11), 4178-4190 is available at https://doi.org/10.3934/era.2022211. |
Appears in Collections: | Journal/Magazine Article |
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era-30-11-211.pdf | 9.43 MB | Adobe PDF | View/Open |
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