Dynamic Programming Approach toward Optimization of Workforce Planning Decisions
Publication: Journal of Construction Engineering and Management
Volume 144, Issue 2
Abstract
Workforce planning plays a pivotal role in smooth execution of construction projects. The growing challenges faced by the construction industry related to skill shortage, aging problem, and workforce attraction, retention, and buy-in have added to technical complexities of workforce planning. Nevertheless, the available workforce planning techniques are either qualitative or lack a strategic perspective that accounts for the above challenges in hiring workforce, leading to suboptimal decisions with regards to hiring and unplanned firing. This paper proposes a novel framework for optimization of hiring and firing decisions by accounting simultaneously for organizational human resource (HR) strategies, labor rights, and technical and managerial constraints of a construction project. The framework starts by setting the model parameters and the decision-making criteria using the information made available by building information modeling (BIM), project performance database, and contractual and legislative documents. It then identifies the optimal mode and duration of the employment for the workers with different skills, skill levels, and multiskilling capabilities using a dynamic programming algorithm. The application and advantages of the proposed framework are demonstrated using a case study.
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Data Availability Statement
All data generated or analyzed during the study are included in the published paper. Information about the Journal’s data sharing policy can be found here: http://ascelibrary.org/doi/10.1061/%28ASCE%29CO.1943-7862.0001263.
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Information & Authors
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Published In
Journal of Construction Engineering and Management
Volume 144 • Issue 2 • February 2018
Copyright
©2017 American Society of Civil Engineers.
History
Received: Jan 19, 2017
Accepted: Aug 7, 2017
Published online: Dec 9, 2017
Published in print: Feb 1, 2018
Discussion open until: May 9, 2018
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