Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/103922
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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.
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