Original scientific paper
https://doi.org/10.1515/otmcj-2016-0026
Genetic algorithm optimization for dynamic construction site layout planning
Panagiotis M. Farmakis
; 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.
Keywords
construction site; layout planning; genetic algorithms; optimization; safety
Hrčak ID:
198175
URI
Publication date:
16.2.2018.
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