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Genetic algorithm optimization for dynamic construction site layout planning

Author

Listed:
  • Farmakis Panagiotis M.

    (School of Science and Technology, Hellenic Open University, Patras 26335, Greece)

  • Chassiakos Athanasios P.

    (Department of Civil Engineering, University of Patras, Patras 26500, Greece)

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.

Suggested Citation

  • Farmakis Panagiotis M. & Chassiakos Athanasios P., 2018. "Genetic algorithm optimization for dynamic construction site layout planning," Organization, Technology and Management in Construction, Sciendo, vol. 10(1), pages 1655-1664, February.
    • Handle: RePEc:vrs:otamic:v:10:y:2018:i:1:p:1655-1664:n:2
    DOI: 10.1515/otmcj-2016-0026
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    References listed on IDEAS

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    1. Ka-Chi Lam & Xin Ning & Thomas Ng, 2007. "The application of the ant colony optimization algorithm to the construction site layout planning problem," Construction Management and Economics, Taylor & Francis Journals, vol. 25(4), pages 359-374.
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