Incorporating Multiskilling and Learning in the Optimization of Crew Composition
Publication: Journal of Construction Engineering and Management
Volume 142, Issue 5
Abstract
The presence of multiskilled workers in a crew can increase the crew’s productivity through reducing inefficiencies and supervision requirements, while also providing on-the-job learning opportunities for single-skilled workers. The effect of the presence of multiskilled workers on the learning rate of workers, which is also a function of skill level and experience, and thus on the crew’s productivity, is especially significant in repetitive construction projects. This paper presents a mathematical model for identifying the optimal combination of single-skilled and multiskilled workers with different levels of experience in the crew to minimize the duration of construction projects by accounting for the overlapping effects of multiskilling, skill level, and learning on the crew’s productivity. The model is applied to an illustrative case project to demonstrate the practicality of the model. The optimum crew compositions for different activities involved in the case project are identified using a solution technique which combines constraint programming (CP), statistical analysis (SA), and a genetic algorithm (GA).
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Information & Authors
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Published In
Journal of Construction Engineering and Management
Volume 142 • Issue 5 • May 2016
Copyright
© 2015 American Society of Civil Engineers.
History
Received: May 22, 2015
Accepted: Sep 18, 2015
Published online: Dec 31, 2015
Published in print: May 1, 2016
Discussion open until: May 31, 2016
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