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The reason these issues are emphasized here is that a modern simulation model can be very flashy and attractive, but its


The reason these issues are emphasized here is that a modern simulation model can be very flashy and attractive, but its
The reason these issues are emphasized here is that a modern simulation model can be very flashy and attractive, but its real value lies in its ability to yield insights into very complex problems.
However, in order to obtain such insights a considerable level of technical skill is required.
A final point to keep in mind with simulation is that it does not provide one with an indication of the optimal strategy.
In some sense it is a trial and error process since one experiments with various strategies that seem to make sense and looks at the objective results that the simulation model provides in order to evaluate the merits of each strategy.
If the number of decision variables is very large, then one must necessarily limit oneself to some subset of these to analyze, and it is possible that the final strategy selected may not be the optimal one.
However, from a practitioner s perspective, the objective often is to find a good strategy and not necessarily the best one, and simulation models are very useful in providing a decision-maker with good solutions.Fassilia
United States. Alabama



day: 19.09.2018
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The reason these issues are emphasized here is that a modern simulation model can be very flashy and attractive, but its

On the other hand, one has to be very careful with simulation models because it is also easy to misuse simulation.
On the other hand, one has to be very careful with simulation models because it is also easy to misuse simulation.
First, before using the model it must be properly validated.
While validation is necessary with any model, it is especially important with simulation.
Second, the analyst must be familiar with how to use a simulation model correctly, including things such as replication, run length, warmup etc; a detailed explanation of these concepts is beyond the scope of this chapter but the interested reader should refer to a good text on simulation.
Third, the analyst must be familiar with various statistical techniques in order to analyze simulation output in a meaningful fashion.
Fourth, constructing a complex simulation model on a computer can often be a challenging and relatively time consuming task, although simulation software has developed to the point where this is becoming easier by the day.Fassilia
United States. Alabama



day: 19.09.2018
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The reason these issues are emphasized here is that a modern simulation model can be very flashy and attractive, but its

Simulation models are analyzed by running the software over some length of time that represents a suitable period when t
Simulation models are analyzed by running the software over some length of time that represents a suitable period when the original system is operating under steady state.
The inputs to such models are the decision variables that are under the control of the decision-maker.
These are treated as parameters and the simulation is run for various combinations of values for these parameters.
At the end of a run statistics are gathered on various measures of performance and these are then analyzed using standard techniques.
The decision-maker then selects the combination of values for the decision variables that yields the most desirable performance.
Simulation models are extremely powerful and have one highly desirable feature they can be used to model very complex systems without the need to make too many simplifying assumptions and without the need to sacrifice detail.Fassilia
United States. Alabama



day: 19.09.2018
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is typically identified with mathematical analysis, the use of an innovative model and problem-solving procedure such as
is typically identified with mathematical analysis, the use of an innovative model and problem-solving procedure such as the one just described is an entirely legitimate way to conduct an O.
Computer Simulation Models With the growth in computational power these models have become extremely popular over the last ten to fifteen years.
A simulation model is one where the system is abstracted into a computer program.
While the specific computer language used is not a defining characteristic, a number of languages and software systems have been developed solely for the purpose of building computer simulation models; a survey of the most popular systems may be found in OR MS Today October 1997, pp.
Typically, such software has syntax as well as built-in constructs that allow for easy model development.
Very often they also have provisions for graphics and animation that can help one visualize the system being simulated.Fassilia
United States. Alabama



day: 19.09.2018
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An army of ants was then released at the anthill and the paths that they chose to get to the mounds of sugar were then o
An army of ants was then released at the anthill and the paths that they chose to get to the mounds of sugar were then observed.
After the model attained a steady state, it was found that the ants by virtue of their own tendencies had found the most efficient paths to their destinations.
One could even conduct some postoptimality analysis.
For instance, various transportation capacities along each link could be analyzed by proportionately varying the width of the link, and a scenario where certain roads were unusable could be analyzed by simply removing the corresponding links to see what the ants would then do.
This illustrates an analogic model.
More importantly, it also illustrates that while O.Fassilia
United States. Alabama



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