This exercise was also contributed by Dr. Rick Wilson of Oklahoma State University to illustrate the

This exercise was also contributed by Dr.
Rick Wilson of Oklahoma State University to illustrate the modelling
capabilities of Excel Solver. National signing day for rugby recruiting season
2018 has been completed. Now, as the recruiting coordinator for the San Diego
State University Aztec rugby team, it is time to analyse the results and plan
for 2019. Youve developed complex analytics and data collection processes and
applied them for the past few recruiting seasons to help you develop a plan for
2019. Basically, you have divided the area in which you actively recruit rugby
players

This exercise was also contributed by Dr.
Rick Wilson of Oklahoma State University to illustrate the modelling
capabilities of Excel Solver. National signing day for rugby recruiting season
2018 has been completed. Now, as the recruiting coordinator for the San Diego
State University Aztec rugby team, it is time to analyse the results and plan
for 2019. Youve developed complex analytics and data collection processes and
applied them for the past few recruiting seasons to help you develop a plan for
2019. Basically, you have divided the area in which you actively recruit rugby
players into eight different regions. Each region has a per-target cost, a
star rating (average recruit star ranking, from 0 to 5, similar to what
Rivals uses for football), a yield or acceptance rate percentage (the
percentage of targeted recruits who come to SDSU), and a visibility measure,
which represents a measure of how much publicity SDSU gets for recruiting in
that region, measured per target (increased visibility will enhance future
recruiting efforts).

Your goal is to create a LINEAR
mathematical model that determines the number of target recruits you should
pursue in each region in order to have an estimated yield (expected number) of
at least 25 rugby recruits for next year while minimizing cost. (Region 1 with
yield of 40%: if we target 10 people, the expected number that will come is
.4*10 = 40.) In determining the optimal number of targets in each region (which,
not surprisingly, should be integer values), you must also satisfy the
following conditions:

No more than 20% of the total targets
(not the expected number of recruits) should be from any one region.

Each region should have at least 4% of
the total targets (again, not the expected number of recruits, but the number
of targets).

The average star rating of the targets
must be at least equal to 3.3.

The average visibility value of the
targets must be at least equal to 3.5.

Off on the recruiting trail you go!

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