# [M B A 8590] - Midterm Exam Guide - Comprehensive Notes for the exam (19 pages long!)

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7 Feb 2017
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Clemson
M B A 8590
MIDTERM EXAM
STUDY GUIDE
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Monday 1/23/17
Decision Modeling 859 Class Notes - #2
- Assignment #1 can be on word or excel but the rest will be excel
- Allows you to take real life problems and optimize the solution
- Whatever assumption you will end up in a different setting it only means that you consider data in a
different way
- Most of the cases are going to be business oriented except for the beginning, it will be math
- Business Analytics has its roots in WWII
- Networking in Supply Chain and Revenue Management is a field that can take a big advantage of this
subject and specifically businesses like airlines, car rental, hotels, etc
- Models
o Mental
o Visual
o Physical
o Mathematical
- In real life modeling there’s no need or way to add every single variable
o At the end we care about maximize profit or minimize cost
- Benefits
o Economy: trial and error in a model is more effective
o Timeliness: solutions to your model is very fast
o Feasibility: you can try anything including impossible things without disturb the
manufacturing process
o Gives you a lot of insights and understanding
- Elements
o Decision Variables: controllable inputs determined by your model
o Objective Function: goal,
Maximizing (profit, revenue)
Minimizing (cost, time)
o Constraints: restrictions
o Unontrollale inputs: e don’t inlude hat e cant control
- You are trying to find the best solution aka optimum solution
- Type of models
o Prescriptive: giving you a solution and you can do whatever you want with it
o Predictive: regression analysis
- Example: Iron Works, math model @6:42pm
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- Equality restricts the model most of the times we will try to de <= or >=
- A onstraint line doesn’t hae to inlude all ariales
o One line can restrict only one variable
- Not limiting constraints to an specific number like using the = sign is what leads toward upper
bounds or lower bounds
Chapter 2: Programming - Basic Concepts
- We are going to face decision about how to use limited resources
o Oil in the earth
o Land for dumps
o Time
o Money
o Workers
- Final goal is to optimize resources for an ultimate goal (max min)
- The graphical method can only handle 2 variables
- Always identified first
o The problem
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