Quiz 1 Preparation Guidelines
Quiz 1 (scheduled on 3/11 Mon.) coverage will
include material identified on the syllabus
through 3/6. In terms of the readings, this
corresponds to chapters 1-5 in our textbook.

Applications of LP (Chapter 3)
 What is product mix problem and how
does it work?
 What is make-buy decision problem and
how does it work?
 What is labor staffing problem and how
does it work?
 What
is
multi-period
production
scheduling problem and how does it
work?

LP Sensitivity Analysis (Chapter 4)
 What’s sensitivity analysis and why is it
important?
 What are the two important types of
sensitivity analysis (i.e., OFC and RHS)?
 What is shadow price and what is
reduced cost?
 What is binding constraint and what is
non-binding constraint?
 What is slack and what is surplus?
 How to use Excel Solver to generate
answer and sensitivity reports and
interpret model results?

Transportation Network Models
(Chapter 5)
 What is transportation model and how
does it work?
 What is transshipment model and how
does it work?
 What is assignment model and how does
it work?
 What is maximal-flow model and how
does it work?
 What is shortest-path model and how
does it work?
 What is minimal-spanning tree model?
The planned format is about 10 true/false and 30
multiple choice questions. The questions, in
general, will emphasize important concepts,
definitions, and logic of LP models.
As far as preparation strategy, I recommend
quickly reviewing sample Quiz 1 questions (can
be downloaded from our class website) and my
lecture notes. Also, read through the following
topic list. Doing these tasks will help focus
attention on some key topics as you review the
material.
Good luck.
Topic List


Introduction to Managerial Decision
Modeling (Chapter 1)
 What is decision modeling?
 What are the types of decision models
(deterministic vs. stochastic/random;
qualitative vs quantitative)?
 What are the key steps in decision
modeling?
 What is break-even analysis?
Linear Programing (LP) Models
(Chapter 2)
 What are the objective function,
decision variables, and constraints of
a LP model?
 What are the feasible region, corner
points, and optimal solution of a LP
model?
 How does graphical method work to
solve LP problems?
 How does Excel Solver work to solve
LP problems