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

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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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