Dynamic Programming Approach toward Optimization of Workforce Planning Decisions

Ahmadian Fard Fini, A; Akbarnezhad, A; Rashidi, TH; Waller, ST

Dynamic Programming Approach toward Optimization of Workforce Planning Decisions

Ahmadian Fard Fini, A

Akbarnezhad, A Rashidi, TH Waller, ST

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Publisher:: American Society of Civil Engineers (ASCE)
Publication Type:: Journal Article
Citation:: Journal of Construction Engineering and Management, 2018, 144 (2), pp. 04017113 - 04017113
Issue Date:: 2018-02

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Field	Value	Language
dc.contributor.author	Ahmadian Fard Fini, A https://orcid.org/0000-0001-7681-1270	en_US
dc.contributor.author	Akbarnezhad, A	en_US
dc.contributor.author	Rashidi, TH	en_US
dc.contributor.author	Waller, ST	en_US
dc.date.issued	2018-02	en_US
dc.identifier.citation	Journal of Construction Engineering and Management, 2018, 144 (2), pp. 04017113 - 04017113	en_US
dc.identifier.issn	0733-9364	en_US
dc.identifier.uri	http://hdl.handle.net/10453/130962
dc.description.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	en_US
dc.language	en	en_US
dc.publisher	American Society of Civil Engineers (ASCE)	en_US
dc.relation.ispartof	Journal of Construction Engineering and Management	en_US
dc.relation.isbasedon	10.1061/(asce)co.1943-7862.0001434	en_US
dc.subject.classification	Building & Construction	en_US
dc.title	Dynamic Programming Approach toward Optimization of Workforce Planning Decisions	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	144	en_US
utslib.for	1202 Building	en_US
utslib.for	0905 Civil Engineering	en_US
utslib.for	1504 Commercial Services	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Design, Architecture and Building
pubs.organisational-group	/University of Technology Sydney/Faculty of Design, Architecture and Building/School of Built Environment
utslib.copyright.status	closed_access
pubs.consider-herdc	false	en_US
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	144	en_US

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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http://hdl.handle.net/10453/130962