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DISC 212 – Introduction to Management Science

Spring 2013

Instructor M. Adeel Zaffar

Room No. 403 – SDSB Building

Office Hours TBAEmail adeel.zaffar@lums.edu.pk  

Telephone 8026

Course Basics

Credit Hours 3

Session(s) Nbr of Lec(s) Per Week(Tuesday/Thursday) A-12

2 Duration 75 min

Labs (Total) 7 Duration 75 min

Tutorials (per week) 1 Duration 90 min

COURSE DESCRIPTIONThis course is designed to provide students with a sound conceptual understanding of the role that

management science plays in the decision making process. It is an important introductory course in

developing decision models and understanding their application to management problems. Theemphasis is on models and techniques that are widely used in all industries and functional areas,

including operations, finance, accounting, and marketing.

COURSE PREREQUISITES

Sophomore standing. A keen interest in problem solving (logic, math, and statistics) and familiarity

with Excel are required.

COURSE OBJECTIVES & LEARNING OUTCOMES

A.  To develop in students an appreciation of the management science approach to problem

formulation and solution

B.  To introduce students to various optimization techniques and particularly develop an

understanding of linear programming problemsC.  To introduce students to basic networking models and their application in business decision

making

D.  To introduce students to Queuing Theory and basic queuing modelsE.  To introduce students to the basic concept of decision analysis and various techniques

involved in evaluating different decision-making scenarios

GRADING BREAKUP

Attendance: 10%

Quizzes: 10%

Project: 10%Exams 1-3 (closed book, closed notes): 50% - lowest exam will be dropped

Final Exam (comprehensive, open book, open notes): 20%

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 Textbook and supplemental material

Spreadsheet Modeling & Decision Analysis by Cliff T. Ragsdale, 5t

Any supplemental material and/or handouts will be made available via Zambeeledition

ATTENDANCEAttendance is required. Frequent absences will not be accepted and the student may be dropped

from the course in the event of 7 or more absences. Students are encouraged to inform the instructorin writing if they have any issues in terms of class attendance.

QUIZZES

All quizzes will be un-announced. No make-up quizzes will be given. Depending on the totalnumber of quizzes given throughout the term, one or two quizzes may be dropped at the end.

Students will not be allowed to make up any missed quiz.

GROUP RPOJECTThe group project will have to be drawn from a real life situation. A 1-2 page project proposal must be submitted by April 4, 2013. Your findings must be presented on April 30

th or May 2

nd . Excel

files and accompanying analysis must be emailed a day before your group’s presentation. Grade on

the project will be awarded on the basis of your presentation and accompanying analysis.

EXAMS

Three in-class exams will be given during the semester. These exams will not be comprehensiveand the lowest score will be dropped. A comprehensive final exam will also be given at the end.

Students will not be allowed to make up any exam.

Please note that the instructor reserves the right to modify any aspect of the course, the syllabusand/or the grading components if he deems it appropriate in view of the progress of the class.

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Planned Lecture Schedule

Date Lec # TopicAssigned

ReadingLearning Outcomes

Tue

Jan 22 1 Course introduction & syllabusIntroduction to Modeling

SyllabusChapter 1

Develop an understanding of

•  Modeling approach towardsdecision making

•  Types of modelsThu

Jan 242

Tue

Jan 293

Introduction to Optimization and

Linear ProgrammingChapter 2

Develop an understanding of

•  The essential elements withinmathematical optimization

•  Characteristics of optimization problems

•  Mathematical programming

•  Basics of Linear programming

(LP)

Thu

Jan 314

LAB LECTURESolving Linear Programming

 problems

Chapter 2Understand the approach towardsmodeling linear programming

 problems

Thu

Feb 75

Modeling and Solving LPs in a

SpreadsheetChapter 3

These lectures will focus on the use

of a spreadsheet to setup a linear

 programming problem. By the endof these lectures, students should be

able to comprehend and model the

following range of problems:

•  Make vs. buy decisions

•  Investment problem•  Transportation problem

•  Blending problem

•  Production and inventory planning problem

•  Multi-period cash flow problem

Tue

Feb 126 LAB LECTURE Chapter 3

Thu

Feb 147 Modeling and Solving LPs Chapter 3

Tue

Feb 198

LAB LECTUREModeling and Solving LPs in a

Spreadsheet

Chapter 3

Thu

Feb 219 Case on Linear Programming -

TueFeb 26

10Exam 1Closed book, closed notes

Chapters 1 – 3

Thu

Feb 28 11 Sensitivity Analysis Chapter 4

Students should be able to

•  Understand the purpose ofsensitivity analysis

•  Analyze the sensitivity reportsgenerated in Excel

•  Appreciate the benefits andlimitations of sensitivity

analysis

Tue

Mar 512

LAB LECTURE

Sensitivity AnalysisChapter 4

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Thu

Mar 713 The Simplex Method Chapter 4

Students should be able to develop

a deeper understanding of the process of solving a linear

 programming problem using the

simplex method.

TueMar 12 14 Introduction to NetworkModeling Chapter 5 These lectures will focusexclusively on a variety of networkmodels. By the end of these lectures

students should be able to model

the following types of problems:

•  Transshipment problem

•  Transportation problem

•  Shortest path problem

•  Equipment replacement problem

•  Generalized network flow

 problem•  Maximal flow problem

•  Minimal spanning trees

ThuMar 14

15LAB LECTURE Network Modeling

Chapter 5

TueMar 26

16

 Network Modeling:

Special Modeling Considerations

Chapter 5

Thu

Mar 2817 Chapter 5

Tue

Apr 218 Case on Network Modeling

Thu

Apr 419

EXAM 2: Closed book, closed

notes

Chapters 4

& 5

Tue

Apr 920

Introduction to Queuing theory Chapter

13

Students should be able to

appreciate the basic dynamics ofsimple queuing models,

characteristics, notation and basic

terminologyThu

Apr 1121

LAB LECTURE

Introduction to Queuing theory

Chapter

13

By the end of these two sessions

students should

•  have a stronger grasp ofcommon queuing models with

multiple servers, different

arrival and service distributions

•   be able to develop queuingmodels in a spreadsheet for real

 problems and critically assess

their performance

TueApr 16

22Chapter13

ThuApr 18

23 Case on Queuing Theory -

Tue

Apr 2324 Decision Analysis

Chapter

15

Students should be able to

understand the basic characteristicsof decision problems and be able to

draw influence diagrams for simple

decision problems

Thu 25 Decision Analysis Chapter Students should have an

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Apr 25 15 understanding of some of the

simpler techniques for solvingdifferent types of decision

 problems:

•  The payoff matrix

•   Non-probabilistic methods•  Probabilistic methods

•  Decision Trees

TueApr 30

26 Project Presentations

ThuMay 2

27 Case on Decision Analysis

Tue

May 728

EXAM 3: Closed book, closed

notes

Chapters

13 and 15

Comprehensive Final Exam: Open book, opennotes