Spreadsheet-Based Decision Support Systems
Chapter 9: Simulation
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Overview
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9.1 Introduction
9.2 Defining Simulation
9.3 Applications
9.4 Summary
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Introduction
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What is simulation and how it is useful
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Performing a simple spreadsheet-simulation using Data Tables and the
Scenario Manager
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Running advanced simulation models from generating random parameter
values from distributions
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Three examples of simulation models
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Defining Simulation
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Data Tables
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Scenario Manager
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Generating Random Numbers within Distributions
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Simulation
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Simulation is a modeling tool which is used to imitate a real-world
process in order to understand system behavior.
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The true behavior of a system is estimated using distributions.
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Random numbers from these distributions can be generated to evaluate
multiple strategies and predict future performance.
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Excel offers two simple tools for performing simulation: Data Tables
and the Scenario Manager.
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Data Tables
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Data Tables are used to determine how some outputs vary in response
to changes in input.
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Data Tables use the spreadsheet to refer to cells which may contain
formulas or functions for some output and input of some problem.
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There are two types of Data Tables:
– one-way data tables: determine how changing one input will change any
number of outputs
– two-way data tables: determine how changing two inputs would change a
single output
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Data Tables (cont)
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A list of inputs and outputs should be created first.
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Next, you will create a list of the various input values you want to
experiment with.
– If you are creating a one-way data table, you would put these values in a
single column.
– If you are creating a two-way data table, you would create one column and
one row of varying input values for the two inputs of interest.
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You must then enter the output formulas you want the Data Table to
calculate for observation.
– For one-way data tables, these output cells would be in the columns
adjacent to the input column.
– For two-way data tables, this output cell would be placed in the upper
corner of the data table.
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Data Tables (cont)
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Select Data > Table from the Excel menu.
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If we are creating a one-way data table, the column input cell will be the
only reference we give.
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If we are creating a two-way data table, we will reference both a row and
column input since we are varying two inputs.
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Figure 9.2
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We are given a list of inputs and outputs for ticket sales.
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The Total Profit is calculated by finding the unit profit (price minus cost
per ticket) and multiplying this value by the number of salespersons and
the average number of tickets sold per person.
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Figures 9.4 and 9.5
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The first data table we want to create will show the different profit values
as we vary the price per ticket. This will be a one-way data table.
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Figures 9.7 and 9.8
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Now suppose we are curious to see how the combination of price per
ticket and number of salespersons affects our total profit; this will now be
a two-way data table.
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Scenario Manager
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The Scenario Manager allows you to vary up to 32 input cells for various
values, or scenarios, and observe the results of several output cells.
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The Scenario Manager will create a Scenario Report which shows the
resulting output values for each scenario of input values.
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Preparation requires an initial list of inputs or outputs. Appropriate values
and formulas should be filled in these cells.
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Then go to Tools > Scenarios to view the Scenario Manager.
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Scenario Manager (cont)
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Add a new scenario.
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Cell references should be to the list
of inputs created in the
spreadsheet preparation.
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Scenario Manager (cont)
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Next, specify the values these inputs should take for the scenario we are
creating.
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Scenario Manager (cont)
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Click Summary to create the Scenario Report.
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The Scenario Summary dialog box asks us to select the outputs we want
to observe for the various scenarios of inputs.
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Figure 9.13
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We are interested in the company’s after tax profits for each of the five
years as well as their total NPV.
We want to consider three different scenarios for year 1 sales, sales
growth, and year 1 price.
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Figures 9.14 and 9.15
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Create each scenario
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Figures 9.16 and 9.17
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After all three scenarios have been created, create the Summary Report.
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Figure 9.18
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The Scenario Report is complete
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Generating Random Numbers
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Some Excel functions can be used to generate various input data values
for several scenarios, or runs of a simulation.
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Once we know the distribution of a certain parameter, we can generate
random numbers within this distribution create the simulation.
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Generating Random Numbers (cont)
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The RAND and RANDBETWEEN functions are used to generate
random numbers in Excel.
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The RAND function does not have any parameters; it returns a randomly
chosen fractional number between 0 and 1.
– =RAND()
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You can manipulate this RAND value if you want to generate values
outside the interval between 0 and 1.
– =RAND()*(n-1) + 1
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Figure 9.19
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To generate heights, widths, and depths to calculate some probable
packaging volumes, we create random numbers between 1 and 10.
– =RAND()*9 + 1
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Generating Random Numbers (cont)
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To generate a random integer, use the INT function with the RAND
function.
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The INT function rounds a number down to the nearest integer.
– =INT(number)
– =INT(range_name)
– =INT(cell_referenced)
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To generate random integers, we would apply the INT function to the
RAND function by typing:
– =INT(RAND())
– =INT(RAND()*(n-1) + 1)
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Generating Random Numbers (cont)
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The RANDBETWEEN function takes two parameters, which are the
lower and upper limits of a range.
– =RANDBETWEEN(lower_limit, upper_limit)
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To create random numbers between 1 and 10, you could type
– =RANDBETWEEN(1,10)
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Generating Random Numbers (cont)
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To generate a random number from a particular distribution, we can use
Excel’s inverse distribution functions.
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The general distribution Excel function is
– =DIST(x_value, distribution_parameters, cumulative_value)
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The general inverse distribution Excel function is
– =DISTINV(probability, distribution_parameters)
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Generating Random Numbers (cont)
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We will use the RAND function as our value for the probability parameter
to generate some number between 0 and 1.
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For example, to generate random numbers from the Normal distribution,
we would follow the format:
– =NORMINV(RAND(), mean, std dev)
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This inverse distribution function can be similarly used for other
distributions:
– BETAINV
– BINOMINV
– LOGINV
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Figure 9.20
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We generate a set of numbers from the Normal distribution with mean 50
and standard deviation 15.
– =NORMINV(RAND(), 50, 15)
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Applications
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News Vendor Problem
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Game of Craps
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Bidding
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News Vendor Problem
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A bookstore must determine how many 2006 comic calendars to order in
September of 2005.
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It costs $2.30 to order each calendar, and they sell each one for $4.70.
After January 1, 2006, any unsold calendars are returned to the supplier
for a salvage value of $0.75 each.
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The best guess is that the number of calendars demanded is governed
by the following probabilities:
– Demand: 150, 200, 250
– Probability: 0.3, 0.3, 0.4
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How many calendars should the company order?
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Figure 9.21
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The spreadsheet is prepared using formulas to determine unknown
values.
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Figure 9.22
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The NORMINV function is used with the RAND function to generate a
random number from the Normal distribution.
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Figure 9.23
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Runs can be made to compare profit values for several random input
values.
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Game of Craps
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In the game of Craps, a player rolls two dice.
If the first roll yields a sum of 2, 3, or 12, the player loses.
If the first roll yields a sum of 7 or 11, the player wins.
Otherwise, the player continues rolling the dice until she matches the
value thrown on the first roll or rolls a sum of 7.
Rolling a match for the first roll wins the game, rolling a value of 7 before
a match loses the game.
How many times will a player win on average in 1, 2, 3, 4, or 5 rolls?
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Figure 9.24
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The conditions for winning and losing on one or multiple rolls are
summarized on the spreadsheet.
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Figure 9.25
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To perform the simulation, the outcome of rolling two dice for 20 different
games is recorded for random results of each game.
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Figure 9.26
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The number of wins can be recorded when 1, 2, 3, 4, or 5 rolls are
played in a game.
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Figure 9.26
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We can create a summary table below the simulation table by counting
the number of wins for each roll among 20 games, or runs.
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To perform this conditional counting, we use the COUNTIF function.
– =COUNTIF(table_range, condition)
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Bidding
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A contractor is planning to make a bid on a construction project.
He believes that it will cost $12,000 to complete the project.
Three competitors are going to bid against him.
Based on past history, he believes that each competitor’s bid is equally
likely to be any value between his cost and triple his cost of completing
the project.
He also believes that each competitor’s bid is independent of the other
bids.
Which bid will maximize his expected profit?
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Figure 9.27
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The inputs and output can be calculated using several formulas.
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Figure 9.28
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Simulation runs can now be generated to find the maximum profit.
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Summary
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Simulation is a modeling tool used for analyzing a process running under
different parameters.
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Scenario Analysis performs all possible alternative actions and notes the
varying results from these different situations.
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To perform random number generation in distributions, use the RAND()
function as the first parameter in the inverse distribution functions.
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Inverse Distribution functions are the following: NORMINV, LN, BETAINV,
BINOMINV.
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Applications of simulation include the News Vendor Problem, Cash
Flows, the Game of Craps, and Bidding.
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Additional Links
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(place links here)
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