Introduction determining the model’s credibility: its advantages and disadvantages,

Introduction

The following essay will examine
the effectiveness of Discrete Event Simulation (DES) and Monte Carlo Simulation
(MCS) in two case studies. It will pay close attention to the applicability and
versatility of both techniques in each case study.  The case studies presented were chosen based
on the writer’s interests.

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First Case Study

In the first case study selected
for this essay the authors developed a model to investigate the financial
structure of a Public- Private Partnership (PPP) young-graduate housing project
in Hangzhou and its associated uncertainties (Xu et al., 2015). The researchers
developed their research methodology after the careful examination of
prevailing PPP models in top tier academic journals dealing with construction,
management and engineering. Developing the research methodology was a long
strenuous process for the authors due to the complexities related to the
project. They found only a handful approaches had been created that identified
the exact financial structure of PPP based apartment construction (Xu et al., 2015).
As a result the researchers opted to take a very conservative approach during
the models construction phase. Ultimately, they chose to utilize a Monte Carlo
Simulation (MCS) that stresses the risk factors of young-graduate PPP housing
project over the construction and operations stages of the venture.

                The MCS
model was evaluated through the interview of several experts from the private,
government, and academic sectors. The interview process permitted the authors
to test the overall logic and applicability of the model in reality. The
experts were given two criteria when determining the model’s credibility: its
advantages and disadvantages, predictability, and reliability. The experts
found the model was well-made and clearly understood the purpose of its applicability
(Xu et al., 2015). Furthermore, they affirmed the model’s logical flow
and reliability over other prevailing PPP models.

                The authors’
selection of the MCS method can be further validated through the examination of
relevant scholarly articles. The MCS is primarily utilized in the field finance
but provides a method for answering any problem where analytical solutions are
not currently available.  According to
Berk and Podhraski (2017), the MCS is a reliable technique for determining
PPP projects “with uneven growth rates of demand and thus cash flow. Determining
the demand for Chinese PPP housing projects is notoriously difficult given the publics’
reluctance to accept public housing owned by the private sector. Consequently,
PPP projects based in China are prime candidates for MCS since forecasting the
demand is problematic, further validating the authors’ method selection (Xu et
al., 2015).

Although the selection of the MCS
method was confirmed through a rigorous validation process the researchers
could have feasibly chosen another technique. For example, the Spanish
construction firm Dragnados has been successfully utilizing discrete event
simulations (DES) on multiple construction projects for several years.
According to Martinez (2010), problems that are appropriate for DES technique
meet the following criteria:

1.      
Involves a great deal of uncertainty due to the
time constraints placed on the project or the amount of materials utilized and
processed.

 

2.      
Logistically complex project with an integrate
set of established rules and decisions.

 

3.      
The project has a series of interconnected parts
contingent on overly complex start-up conditions in which resources with unique
properties work in concert to a set of dynamic rules

Given the complex uncertainties associated with the PPP
project and the fact it meets all of the above criteria makes it a good
candidate for the DES technique.

Second Case Study

The second paper selected for
this essay applies a simulation based method for the modelling of temporary
storage facilities that house resources at construction sites. The study analyses
the effects of storage facility size on construction projects and attempts to
create a model that addresses storage space limitations (RazaviAlavi and
AbouRizk, 2015).  The paper’s
authors embraced a hybrid simulation approach that combines a continuous simulation
(CS) and discrete event simulation (DES) to correctly model the material flow
and managerial activity. The approach incorporates all of the constraints a typical
construction project would face such as site layout, logistical issues, and
material management. The hybrid approach that incorporates DES was taken due to
the uncertainties a vast majority of construction projects face.

                To test
the accuracy of the hybrid model they applied it to the layout process of a proposed
tunnel project. Traditionally, tunnelling projects involve the flow of two materials:
segments (concrete liners) and soil (RazaviAlavi and AbouRizk, 2015). The soil portion
involves the excavation, storage, and removal of soil material from the project
site. On other hand, the segment portion involves the storage, delivery, and
installation of the segments on site. Since the soil and segment flows are occurring
simultaneously this creates a great deal of uncertainty for the project. For
instance trying to incorporate segment and soil flow rates, TBM penetration
rate, and resource implementation make it difficult to model the project. The DES
technique was applied to the tunnelling duty at the operating level to determine
the tunnel production rate.

                Due to
the complex nature of the tunnelling project and hybrid approach utilized by
the researchers another simulation method could have feasibly been employed.  Given the complexity of the tunnelling project
the MCS could have to been used as a substitute for one of other techniques.
For instance, Isakkson and Stille (2005) constructed a MCS model to estimate
the construction times and cost outcomes of tunnelling projects. In order to
test the robustness of the model it was applied to the Grauholz Tunnel project
in Switzerland. The time and cost estimations produced by the model were
compared with the actual estimation results obtained from the planning stages
of the tunnelling project. The estimations produced from the MCS model were similar
to the actual project results. This indicates that an MCS can successfully
employed on a tunnelling project especially when a great degree of uncertainty is
present.

Conclusion

This essay has successfully shown the applicability and versatility
of both techniques in the field of construction.  The techniques are useful tools when
attempting to simulate complex projects.