What is quantitative Analysis and Decision making?
1.
Decision making
a.
Structuring the problem:
a.i.
a.ii.
Identity the alternatives
a.iii.
b.
Define the problem
Determine the criteria
Analyzing the problem
b.i.
b.ii.
c.
Identity the alternatives
Choose
TEAM CONTRACT
Project Management (Tuesday)
A.
Project Leader:
Commitments
As a project team we will:
1. Only agree to do work that we are qualified and capable of doing.
2. Be honest and realistic in planning and reporting project scope and schedule.
3. O
Team Charter Project Management (Tuesday)
Group members:
Duration & Time Commitment
The first line of communication outside of class should be email, and then text if need be.
Meeting times outside of class will contingent upon the flexibility of the grou
Model development
1.
Models are representation of real objects or situations
a.
Three forms of models are
a.i.
Ionic models: physical replicas (scalar
representations of real objectives.
a.ii.
Analog models: physical in form but do not
physically resemble
1.
Deterministic Model: if all uncontrollable inputs
to the model are known and cannot vary.
2.
Stochastic (or probabilistic) model: if any
uncontrollable are uncertain and subject to
variation.
a.
Stochastic models are often more difficult to
analyze.
b.
Mathematical Models Class Notes Continue
1.
What are constraints?
a.
Constraints are a set of restrictions or
limitation, such as production capacities.
a.i.
To continue our example, a production
capacity constraint would be
necessary if, for instance, 5
1.
2.
Trial and error solution for production problems
Model Solution
a.
A variety of software packages are available
for solving mathematical models.
b.
What is a Lingo?
b.i.
3.
Its a software packages
Model testing and validation
a.
Often, goodness/ acc
Models of cost, Revenue and Profit
1.
Mathematical model:
a.
The total monthly profit = (profit per unit of
Product 1) * (monthly production of
product 1) + ( profit per unit of product 2)
* ) monthly production of product 2) =
= p1x1 + P2X2
2.
We want to
Management Science Techniques Part 2
1.
Waiting line ( for queuing) models
a.
Help managers understand and make better
decisions concerning the operations of
systems involving waiting lines.
b.
Simulation
b.i.
Is a technique used to model the
operation of
Management Science Techniques
1.
Linear Programming:
a.
is a problem solving approach developed for
situation involving maximizing or
minimizing a linear function subjects to
linear constraints that limit the degree to
which the objective can be pursued.
Chapter 1
1.
Body of knowledge:
a.
The body of knowledge involving quantitative
approaches to decision making is referred to as
a.i.
a.ii.
Operations research
a.iii.
b.
Management science
Decision science
It had its early roots in world war 2 and its
flou