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Organization, Technology and Management in Construction: an International Journal

Co-published with University of Zagreb, Faculty of Civil Engineering

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1847-6228
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Genetic algorithm optimization for dynamic construction site layout planning

Panagiotis M. Farmakis / Athanasios P. Chassiakos
Published Online: 2017-12-29 | DOI: https://doi.org/10.1515/otmcj-2016-0026

Abstract

The dynamic construction site layout planning (DCSLP) problem refers to the efficient placement and relo­cation of temporary construction facilities within a dynam­ically changing construction site environment considering the characteristics of facilities and work interrelationships, the shape and topography of the construction site, and the time-varying project needs. A multi-objective dynamic opti­mization model is developed for this problem that considers construction and relocation costs of facilities, transportation costs of resources moving from one facility to another or to workplaces, as well as safety and environmental consider­ations resulting from facilities’ operations and interconnec­tions. The latter considerations are taken into account in the form of preferences or constraints regarding the prox­imity or remoteness of particular facilities to other facilities or work areas. The analysis of multiple project phases and the dynamic facility relocation from phase to phase highly increases the problem size, which, even in its static form, falls within the NP (for Nondeterministic Polynomial time)- hard class of combinatorial optimization problems. For this reason, a genetic algorithm has been implemented for the solution due to its capability to robustly search within a large solution space. Several case studies and operational scenar­ios have been implemented through the Palisade’s Evolver software for model testing and evaluation. The results indi­cate satisfactory model response to time-varying input data in terms of solution quality and computation time. The model can provide decision support to site managers, allowing them to examine alternative scenarios and fine-tune optimal solutions according to their experience by introducing desir­able preferences or constraints in the decision process.

Keywords: construction site; layout planning; genetic algorithms; optimization; safety

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About the article

Received: 2017-09-14

Accepted: 2017-11-24

Published Online: 2017-12-29

Published in Print: 2017-12-20


Citation Information: Organization, Technology and Management in Construction: an International Journal, Volume 9, Issue 1, Pages 1655–1664, ISSN (Online) 1847-6228, DOI: https://doi.org/10.1515/otmcj-2016-0026.

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© 2018. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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