COURSE SYLLABUS
IS3310 (Quantitative Analysis)
Department of Information System
Salman Ben Abdulaziz University
Course
description:
The main purpose for this course is to introduce the main concepts of quantitative
analysis models. The course covered topics related to decision making models:
decision trees, inventory, linear programming, network planning, decision making
under uncertainty; expected utility theory, transportation, waiting lines, and
simulation.
Prerequisites:
Co-requisite:
STAT1050
Course
Learning
Outcomes
Student completing this course successfully will be able to :
CLO1. Define quantitative analysis approach and it is applications in a real
situation.
CLO2. Outline roles of modeling in quantitative analysis
CLO3. Design accurate and useful decision models
CLO4. Design linear programming model and Graphically solve any LP problem
CLO5. Calculate inventory economic order quantity (EOQ) and reorder point (ROP).
CLO6. Analyze and solve networks models and find out the minimal-spanning
tree, maximal-flow and short route.
CLO7. Calculate solution Using the northwest corner, VAM, MODI, and steppingstone methods
CLO8. Analyze and solve queuing and waiting problems
CLO9. Develop random number intervals and use them to generate outcomes in
Monte Carlo Simulation
List of Topics
Topics covered
Introduction to Quantitative Analysis :
 Define Quantitative Analysis and the Quantitative
Analysis Approach
 The Role of Computers and Spreadsheet Models in the
Quantitative Analysis Approach
 Possible Problems in the Quantitative Analysis
Approach
Decision Analysis:
 The Six Steps in Decision Making
 Types of Decision-Making Environments
 Decision Making under Uncertainty
 Decision Making under Risk
 Decision Trees
No. of Weeks
1
2
Inventory Control Models:
 Inventory Decisions
 Economic Order Quantity: Determining How Much to
Order
 Reorder Point: Determining When to Order
 Quantity Discount Models
Linear Programming Models: Graphical and Computer Methods:
 Requirements of a Linear Programming Problem
 Formulating LP Problems
 Graphical Solution to an LP Problem
Transportation Models
 Setting Up a Transportation Problem
 Developing an Initial Solution
 Unbalanced Transportation Problems
 Maximization Transportation Problems
Network Models:
 Minimal-Spanning Tree Technique
 Maximal-Flow Technique
 Shortest-Route Technique
Waiting Lines and Queuing Theory Models
 Waiting Line Costs
 Characteristics of a Queuing System
 Single-Channel Queuing Model with Poisson Arrivals
and Exponential Service Times (M/M/1)
Simulation Modeling
 Advantages and Disadvantages of Simulation
 Monte Carlo Simulation
 Simulation and Inventory Analysis
 Simulation of a Queuing Problem
 Simulation Model for a Maintenance Policy
2
2
2
1
2
2
Class/Tutorial
Schedule :
15 week semesters, classes meet 2 days per week for (3 x 50) minute lectures
and one day per week for 50 minute
Textbook :
Render, Stair, and Hanna (2009). Quantitative Analysis for Management, Tenth Edition,
Prentice-Hall, Inc.
References:
Hamdi Taha (2005) " Introduction to Operations Research" Printice Hall, USA.
Relationship of Course learning outcomes to Student outcomes
Student Outcomes
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Course Learning Outcomes (CLOs)
Define quantitative analysis approach and it is
applications in a real situation.
Outline roles of modeling in quantitative analysis.
Design accurate and useful decision models
Calculate solution Using the northwest corner, VAM,
MODI, and stepping-stone methods
Calculate inventory economic order quantity (EOQ)
and reorder point (ROP).
Design linear programming model and Graphically
solve any LP problem.
Analyze and solve networks models and find out the
minimal-spanning tree, maximal-flow and short route.
Analyze and solve queuing and waiting problems
Develop random number intervals and use them to
generate outcomes in Monte Carlo Simulation
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Proportion
Second exam
Tutorial + quizzes +
Week 11
During the term
20%
20%
Final exam
Week 15
40%
Office hours:
Location
Room CF13
Time
Monday 8:00 to 10:00 am , and, Tuesday 9:00 to 10:00am,
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20%
Reviewed by:
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Week 5
Dr. Elsadig Abdalla Aljack
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First exam
Prepared by :
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Course evaluation : There are two exams during the term, a final exam, and quizzes:
Week due
f
First semester 35-36H.