Management science modeling lecture one
This presentation is the property of its rightful owner.
Sponsored Links
1 / 29

Management Science Modeling Lecture One PowerPoint PPT Presentation


  • 90 Views
  • Uploaded on
  • Presentation posted in: General

Management Science Modeling Lecture One. Introduction to Modeling (Chapter One). Chapter Topics. The Management Science Approach. The Management Science Process. Figure 1.1. Steps in the Management Science Process. Example of Model Construction (1 of 3). Information and Data:

Download Presentation

Management Science Modeling Lecture One

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Management science modeling lecture one

Management Science Modeling Lecture One

Introduction to Modeling

(Chapter One)

MS Modeling S 2010


Chapter topics

Chapter Topics

MS Modeling S 2010


The management science approach

The Management Science Approach

MS Modeling S 2010


The management science process

The Management Science Process

Figure 1.1

MS Modeling S 2010


Management science modeling lecture one

Steps in the Management Science Process

MS Modeling S 2010


Example of model construction 1 of 3

Example of Model Construction (1 of 3)

  • Information and Data:

  • Business firm makes and sells a steel product

  • Product costs $5 to produce

  • Product sells for $20

  • Product requires 4 pounds of steel to make

  • Firm has 100 pounds of steel

  • Business Problem:

  • Determine the number of units to produce to make the most profit, given the limited amount of steel available.

MS Modeling S 2010


Management science modeling lecture one

Example of Model Construction (2 of 3)

Variables:X = # units to produce (decision variable)

Z = total profit (in $)

Model:Z = $20X - $5X (objective function)

4X = 100 lb of steel (resource constraint)

Parameters:$20, $5, 4 lbs, 100 lbs (known values)

Formal Specification of Model:

maximize Z = $20X - $5X

subject to 4X ≤ 100

MS Modeling S 2010


Management science modeling lecture one

Example of Model Construction (3 of 3)

Model Solution:

Solve the constraint equation:

4x ≤ 100

(4x)/4 ≤ (100)/4

x ≤ 25 units

Substitute this value into the profit function:

Z = $20x - $5x

= (20)(25) – (5)(25)

= $375

(Produce 25 units, to yield a profit of $375)

MS Modeling S 2010


Management science modeling lecture one

Model Building:

Break-Even Analysis (1 of 9)

  • Used to determine the number of units of a product to sell or produce that will equate total revenue with total cost.

  • The volume at which total revenue equals total cost is called the break-even point.

  • Profit at break-even point is zero.

MS Modeling S 2010


Management science modeling lecture one

Model Building:Break-Even Analysis (2 of 9)

Model Components

  • Fixed Cost (cf) - costs that remain constant regardless of number of units produced.

  • Variable Cost (cv) - unit production cost of product.

  • Volume (v) – the number of units produced or sold

  • Total variable cost (vcv) - function of volume (v) and unit variable cost.

MS Modeling S 2010


Management science modeling lecture one

Model Building:Break-Even Analysis (3 of 9)

Model Components

  • Total Cost (TC) - total fixed cost plus total variable cost.

  • Profit (Z) - difference between total revenue vp (p = unit price) and total cost, i.e.

MS Modeling S 2010


Management science modeling lecture one

Model Building:Break-Even Analysis (4 of 9)

Computing the Break-Even Point

The break-even point is that volume at which total revenue equals total cost and profit is zero:

The break-even point

MS Modeling S 2010


Management science modeling lecture one

Model Building:

Break-Even Analysis (5 of 9)

Example:Western Clothing Company

Fixed Costs: cf = $10000

Variable Costs: cv = $8 per pair

Price : p = $23 per pair

The Break-Even Point is:

v = (10,000)/(23 -8)

= 666.7 pairs

MS Modeling S 2010


Management science modeling lecture one

Model Building:

Break-Even Analysis (6 of 9)

Figure 1.2

MS Modeling S 2010


Management science modeling lecture one

Model Building:

Break-Even Analysis (7 of 9)

Figure 1.3

MS Modeling S 2010


Management science modeling lecture one

Model Building:

Break-Even Analysis (8 of 9)

Figure 1.4

MS Modeling S 2010


Management science modeling lecture one

Model Building:

Break-Even Analysis (9 of 9)

Figure 1.5

MS Modeling S 2010


Management science modeling lecture one

Break-Even Analysis: Excel Solution (1 of 5)

Exhibit 1.1

MS Modeling S 2010


Management science modeling lecture one

Break-Even Analysis: Excel QM Solution (2 of 5)

Exhibit 1.2

MS Modeling S 2010


Management science modeling lecture one

Break-Even Analysis: Excel QM Solution (3 of 5)

Exhibit 1.3

MS Modeling S 2010


Management science modeling lecture one

Break-Even Analysis: QM Solution (4 of 5)

Exhibit 1.4

MS Modeling S 2010


Management science modeling lecture one

Break-Even Analysis: QM Solution (5 of 5)

Exhibit 1.5

MS Modeling S 2010


Management science modeling lecture one

Classification of Management Science Techniques

Figure 1.6 Modeling Techniques

MS Modeling S 2010


Management science modeling lecture one

Characteristics of Modeling Techniques

  • Linear Mathematical Programming -clear objective; restrictions on resources and requirements; parameters known with certainty. (Chap 2-6, 9)

  • Probabilistic Techniques -results contain uncertainty. (Chap 11-13)

  • Network Techniques - model often formulated as diagram; deterministic or probabilistic. (Chap 7-8)

  • Other Techniques - variety of deterministic and probabilistic methods for specific types of problems including forecasting, inventory, simulation, multicriteria, etc. (Chap 10, 14-16)

MS Modeling S 2010


Management science modeling lecture one

Business Use of Management Science

  • Some application areas:

    - Project Planning

    - Capital Budgeting

    - Inventory Analysis

    - Production Planning

    - Scheduling

  • Interfaces - Applications journal published by Institute for Operations Research and Management Sciences (INFORMS)

MS Modeling S 2010


Management science modeling lecture one

Decision Support Systems (DSS)

A decision support system is a computer-based system that helps decision makers address complex problems that cut across different parts of an organization and operations.

Features of Decision Support Systems

  • Interactive

  • Use databases & management science models

  • Address “what if” questions

  • Perform sensitivity analysis

    Examples include:

    ERP – Enterprise Resource Planning

    OLAP – Online Analytical Processing

MS Modeling S 2010


Management science modeling lecture one

Management Science Models

Decision Support Systems (2 of 2)

Figure 1.7 A Decision Support System

MS Modeling S 2010


Do you have any questions about this chapter

Do you have any questions about this chapter?

MS Modeling S 2010


Assignment for chapter one

Assignment for Chapter One

Problems #4, 10, 12, 22, and 24

MS Modeling S 2010


  • Login