MGOC10H3 Lecture Notes - Lecture 1: Dynamic Programming, Standard Deviation, Goal Programming

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26 May 2017
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MGOC10 Analysis for Decision Making
Lecture 01
Chapter 1 Introduction to Quantitative Decision Making
Outline:
Body of Knowledge
Problem Solving and Decision Making
Qualitative VS Quantitative Approach
Quantitative Analysis
Management Science Techniques
Body of Knowledge
Body of knowledge involving quantitative approaches to decision making is referred to as
Management Science
Operations Research
Decision Science
It had its early roots in World War II and is flourishing in business and industry due to:
Numerous methodological developments (e.g. simplex method for solving linear
programming problems)
Virtual explosion in computing power which allows large practical problems to be solved
Management Science Techniques
Linear Programming
Integer Linear Programming
PERT/CPM
Inventory Models
Waiting Line Models
Simulation
Decision Analysis
Goal Programming
Analytic Hierarchy Process
Forecasting
Markov-Process Models
Dynamic Programming
Quantitative Analysis and Decision Making Steps
1. Define the Problem
2. Identify the Alternatives
3. Determine the Criteria
4. Evaluate the Alternatives
5. Choose an Alternative
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Qualitative VS Quantitative Approach & reasons for Quantitative Approach
Qualitative Approach to decision making
based largely on the manager’s judgment and experience
includes the manager’s intuitive “feel” for the problem
is more of an art than a science
Example
A Store Manager needs to come up with a schedule for which employee is working on
which day for next week.
If the Manager has been working in the store for long time, he/she maybe able to come up
with a schedule based on experience.
Manager would know to make staffing adjustments due to special holidays.
Quantitative Approach to decision making
Analyst will concentrate on the quantitative facts or data associated with the problem
Analyst will develop mathematical expressions that describe the objectives, constraints,
and other relationships that exist in the problem
Analyst will use one or more quantitative methods to make a recommendation
Example
A Store Manager develops a linear-integer programming model to determine how to
schedule employees for the store next week.
The Manager input data such as: sales forecast for the next 7 days into the model,
employee availability and paid rates.
The model will include constraints such as: full time employees need to be assigned at
least 30 hours / week, John and Mary don’t like each other so don’t schedule them on
same shift.
Potential Reasons for a Quantitative Analysis Approach to Decision Making
The problem is complex
The problem is very important
The problem is new
The problem is repetitive
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