MGM3163 (Quantitative Techniques), Semester 1 2014-2015, PAGE 1

MGM3163(QUANTITATIVE TECHNIQUE) Syllabus

Semester 2 2013-2014

Instructor: Mrs Manisah Othman Office: Block A 231

Phone: 7694

e-mail: ;

Office Hours: Mondays - Thursday 9:00 - 12:00, 2.00 - 5:00

Fridays 9:00 - 11:45, 3:00 - 5:00

Text: Taylor, B. (2013). Introduction to Management Science. (11th ed.). New Jersey: Prentice Hall.

Course Description: This course discusses the quantitative models as tool for decision makings that will cover issues of model formulation probability concepts, expected and conditional value, decision theory, inventory control, linear programming using simplex method, dual problem and sensitivity analysis, transpotation model, game theory, queuing theory, simulation and PERT/CPM

Prerequisite: MTH 3004.

Course Objectives:

  1. Describe the business problem in mathematical models
  2. Solve a mathematical model using the appropriate technique.
  3. Using a computer package to solve a variety of mathematicalmodels.
  4. Distinguish between different business problems and use appropriate modeling techniques

Course Outline:

  1. Introduction to Management Science (Chapter 1)
  1. Decision making; discipline of management science
  2. Model building; breakeven analysis
  1. Modeling with Linear Programming (Chapter 2)

A. Model Formulation

B.Graphical method (maximization & minimization)

Course Outline (continued)

  1. Linear Programming : Sensitivity Analysis (Chapter 3)
  1. Computer Solution
  2. Sensitivity Analysis.
  1. Linear Programming : Product Mix (Chapter 4)
  2. Product Mix Example
  3. A Diet Example
  4. An Investment Example
  5. A Marketing Example
  1. Linear Programming : Transportation Problems (Chapter 6)
  1. The Transportation Model
  2. The Transshipment Model
  3. The Assignment Model
  1. Network Model (Chapter 7)
  1. Shortest Route Problem
  2. The Minimal Spanning Tree Problem
  3. The Maximal Flow Problem
  1. Managing Projects (Chapter 8)
  2. The Element of Project Management
  3. CPM/PERT
  4. Probabilistic Activity Times
  5. Project Crashing
  1. Decision Making Models (Chapter 12)
  2. Components of Decision Making
  3. Decision Making Without Probabilities
  4. Decision Making With Probabilities
  1. Waiting Line (Chapter 13)
  2. Elements Of Waiting Line Analysis
  3. Single Server
  1. Simulation (Chapter 14)
  1. The Monte Carlo Process
  2. Continuous Probability Distribution

Testing and Grading: Each student's grade will be determined by the number of points that he/she accumulated during the semester. There will be total 100 possible points derived from the following sources: mid-term, homework, tutorial, project and a final exam. The final exam will cover topics discussed after the previous test.

The overall grade will be computed as follows

Midterm exam30%

Final exam 40%

Project 15%

Homework15%

Total 100%

Project (Individual)

The objective of this project is to develop the skill to structure a practical problem. The student will identify a business problem (personal business is also acceptable), and use one of the methods covered in this course to structure a spreadsheet that can be used to support decision making to solve this problem. An example of such a problem could be which health insurance plan you should choose in light of their premiums and benefits. Another example could be about optimal financial portfolio analysis of various investment options. Yet another example would be to support decisions for how many items to keep of each SKU in a category in the inventory - when we have an idea of the demand and substitution patterns for these items. It is not absolutely necessary to have actual data for the problem,realistic values for model input parameters can be determined based on qualitative research results.

Students can discuss their project topic ideas with the instructor to get feedback. The project teams/ individual students will prepare a short project proposal identifying the topic - the decision problem with the objective, decisions to be made, and important issues to be considered including assumptions, constraints, deterministic or probabilistic nature and the planning horizon, by week 6 and will discuss in class. The students will present their work in class in the last week of classes. The final report and the spreadsheet are due in the finals week. The report should be a maximum of five pages with the following contents:

  • definition of the business problem with the key issues and the key question;
  • description the spreadsheet model and how it helps answer the key question;
  • description of the data needs – essentially the inputs of the model;
  • list of model assumptions and an assessment of how appropriate they are for the business situation, including the determination of two model parameters for sensitivity analysis
  • sensitivity analysis on the two key parameters of the model
  • recommendation on the key question based on the model output and sensitivity analysis