posted on 2010-12-07, 11:23authored byMargaret W. Emsley
This thesis describes the development of a descriptive mathematical model to
determine the optimum position of a single tower crane. The objective function of
the model is that of minimization of total travel time necessary to complete all
movements from the installation of the crane until it is dismantled and removed.
Previous models which have been developed to determine optimum crane selection and
location are categorized as simulation models, expert systems and mathematical models
and three particular models are credited as making contributions to the problem of
tower crane location. However, the model developed here overcomes many of the
deficiencies exhibited by these models.
In developing a model to determine optimum tower crane location, the characteristics of
the construction site in which it will be placed and those of the crane itself must be
considered separately. The most challenging and significant problem is in determining
the total number of movements which will occur during the time when a particular
crane is installed on a particular site. The method adopted was the application of a linear
programming technique, the Simplex Method.
Once the (computer) model had been developed a wide range of simulations were
carried out to see if any general truth concerning the optimum layout could be
evinced. The result of these simulations demonstrated that there are potentially
significant savings to be made, in terms of the time to complete all movements, by
locating the crane in the optimum position rather than in one where the maximum
time to complete all movements occurs. Typical savings were in the order of 30% but
situations where the time savings were in excess of 100% and even 200% were not
uncommon. The layout configuration was shown to have very little influence on the
magnitude of the minimum time to complete all movements. And these optimum
positions were found to consistently occur at the site perimeter, very often at the
corners, whilst the positions associated with the maximum times were consistently
located internally. However, when the cost implications of locating the crane at the
perimeter, which necessitates the use of a crane with a longer jib than would be
necessary were the crane located internally, were taken into account, it was shown
that, in terms of cost benefits, the cheaper option is to use the crane with a short a jib
as is viable for the purposes of reaching the points the crane is required to service,
and locate the crane internally.
Finally, neural networks were shown to have potential as a tool to predict optimum
crane location, but further work is needed to produce a working model.