Multiobjective Dynamic-Guiding PSO for Optimizing Work Shift Schedules
Publication: Journal of Construction Engineering and Management
Volume 144, Issue 9
Abstract
Work shift system is commonly used in construction projects to meet project deadlines. However, evening and night shifts raise the risk of adverse events and thus must be used to the minimum extent feasible. The three objectives of the work shift problem are to minimize project duration, project cost, and total evening and night shift work hours while effectively handling relevant scheduling constraints. This study proposes a new multiobjective approach that hybridizes dynamic guiding, chaotic search, and particle swarm optimization (PSO) functions, named multiobjective dynamic guiding chaotic search particle swarm optimization (MO-DCPSO). The approach can overcome the drawbacks of PSO in solving discrete domain problems and recruit more nondominated solutions kept in the archive. A real case was employed to verify the robustness and efficiency of the proposed approach. The result also indicated that MO-DCPSO is more fitting for solving practical project control issues.
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Data Availability Statement
Data generated or analyzed during the study are available at https://doi.org/10.1016/j.autcon.2009.12.015. Information about the Journal’s data sharing policy can be found here: http://ascelibrary.org/doi/10.1061/(ASCE)CO.1943-7862.0001263.
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Information & Authors
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Published In
Journal of Construction Engineering and Management
Volume 144 • Issue 9 • September 2018
Copyright
©2018 American Society of Civil Engineers.
History
Received: Jul 27, 2017
Accepted: Apr 10, 2018
Published online: Jul 9, 2018
Published in print: Sep 1, 2018
Discussion open until: Dec 9, 2018
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