COURSE UNIT TITLE

: MANAGEMENT SCIENCE

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
UQM 2001 MANAGEMENT SCIENCE COMPULSORY 3 0 0 5

Offered By

BUSINESS ADMINISTRATION (UOLP-SUNY ALBANY)

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR SABRI ERDEM

Offered to

BUSINESS ADMINISTRATION (UOLP-SUNY ALBANY)

Course Objective

The course aims to provide students the basics of linear programming and management science tools for solving business-oriented optimization problems.

Learning Outcomes of the Course Unit

1   Have a knowledge understanding the basic concepts of mathematical models, linear programming methods
2   Be able to use essential tools of linear programming for making business decisions.
3   Employ critical thinking and independent problem-solving skills to optimize real world business problems.
4   Be able to use Spreadsheet Software and a solver to perform analysis and support presentations.
5   Communicate clearly the results of an basic optimization methods and explain the managerial implication.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to course Basic Concepts and Model Building Start group selection for case analysis Lecture Contents: (Basic Concepts of Optimization Types of Models Types of Mathematical Models Building Mathematical Models)
2 Introduction to Linear Programming Lecture Content: (LP Models, Assumptions of LP, Demonstrating LP Models Graphically, Optimize LP Graphically, Applying Sensitivity Analysis Analytically Special Case Analysis of LP) Assigning case studies to the groups
3 LP Applications in Business Lecture Content: (Investment and Portfolio Problems, Timetable Scheduling, Diet Problems, Assignment and Product Mix Problems)
4 Simplex Method Lecture Content: (Canonical Form of LP, Basic and Non-Basic Variables, Slack and Surplus Variables, Simplex Table, Deciding Pivot Row, Column and Values, Applying Matrix Row Elimination Method, Entering-Leaving Variables, Deciding Optimum Table, Differing Alternative Solution, Degeneracy, Unfeasible and Unbounded Solution, Working with Minimization Problems)
5 Duality and Sensitivity Analysis Lecture Content: (DUALITY: Duality, Primal-Dual Relationships, Economical Interpretations, Converting Minimization and Maximization Problems into Each Other, SENSITIVITY: Interpretation of Optimum Simplex Table, Shadow Price, Reduced Cost, Changing RHS and Objective Function Coefficients, 100% Rule) Computer Lab Applications: Introducing Excel Solver
6 Solving Minimization Problems Lecture Content: (Big M Method, Dual Simplex, Two Phase Method) Review Session
7 Solving Integer Problems Lecture Content: (Types of Integer Problems, Graphical Demonstration, Gomory Cutting Plane Method, Branch and Bound Method, Enumeration Method)
8 Transportation and Assignment Algorithms Lecture Content: (TRANPORTATION ALGORTIMHS: Describing and Modeling Transportation Problems, Balanced and Unbalanced Cases, LP Formulation, NWC, Least Cost, VAM, Stepping Stone and MODI Methods ASSIGNMENT ALGORITHMS: Describing and Modeling Assignment Problems, Balanced and Unbalanced Cases, LP Formulation, Hungarian Algorithm, Solving Maximization Problems)
9 Project Planning Lecture Content: (Project Scheduling, Earliest and Latest Start and Finish Times, Critical Path, CPM, Three Time Estimation, Beta Distribution and PERT )
10 Project Crashing Lecture Content: (Project Crashing, Crashing Methods, Resource Balancing) Review Session
11 Queue Theory Lecture Content: (Basic Queue Terms, Performance Indicators, Basic Queue Types, M/M/1, M/M/K queues, Optimizing cost of M/M/k queue) Computer Lab Applications
12 Case Study Presentations Lecture Content: (Presentation of Case Reports Peer Evaluations)

Recomended or Required Reading

1. Text Books:
Introduction to Management Science, Hillier and Hillier, 2010, Pearson Education.
Işletme Problemleri için Optimizasyon -Adım Adım Uygulama Örnekleriyle, Sabri ERDEM, Makina Mühendisleri Odası Yayınları, 2010
Introduction to Operations Research, by Hillier & Hillier, Lieberman, McGraw-Hill 2000 and later
Introduction to Management Science 7th Ed. By Bernard W. Taylor III, Pearson Education
Operations Research an Introduction, 9th Edition by Hamdy A. TAHA
Sayısal Yöntemler: Yönetsel Yaklaşım by Ş. GÜMÜŞOĞLU, H. TÜTEK, 2008-2010, Beta Yayıncılık
2. Lecture Slides:
Complementary of the text book.
3. Software:
Spreadsheet Software with Solver add-in.
Lindo/Lingo (optional)
4. Calculator:
Students will need a scientific calculator for various calculation problems in and out of class, and during exams.

Planned Learning Activities and Teaching Methods

1. Lectures
Class lecture is highly interactive and format is direct. The instructor prompts students for response to questions
posed and solicits their thoughts on issues discussed. Lectures will focus on the transfer of basic optimization
concepts and techniques where comprehension is substantially enhanced by additional elaboration and
illustration. The emphasis is on business applications rather than rigorous mathematics.
2. Review Sessions and Class Discussions
Review sessions will be handled by the instructor each week in the last session of a lecture. In-class assignments
and homework assignments are the basis of problems to be solved in these sessions. Individual participation by
students in classroom discussion is strongly encouraged.
3. Computer Applications
In the laboratory component, Spreadsheet Software with solver add-in and a particular solver package will be
introduced to construct optimization models. Instruction on the use of this software as it relates to optimization
problems will be provided in class and in the book.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1
2
3
4
5
6
7


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

1. Exams
There will be two exams during the semester.
Midterm Exam (%30)
Final Exam (%30)
Exams will measure the ability to identify and apply the appropriate technique and/or method to real world business problems. Each exam will cover course materials and include problems
like those assigned for homework, questions on lecture materials, and additional items covered in class meetings.

2. Home works and Participation
Homework problems will be assigned frequently. It is imperative that you work and understand these problems to successfully complete the course. It is strongly recommended the students to work all homework problems as a study tool for the exams.
By completing homework assignments, each student will enhance analytical skills, as well as, improve competency utilizing Spreadsheet Software with solver add-in and a solver package for optimization and analysis. By actively participating in class discussions and in-class assignments, each student will improve communication and analytical skills through learning optimization concepts and business applications.

3. Case Analysis
Case studies will offer an excellent opportunity for students to perform analysis, model formulation and develop solutions to realistic situations. For the case analysis, a group including three students should be formed. Any deviation from this target number requires approval of the instructor. The cases will be assigned to each group by the instructor in the beginning of the semester. Topics consist of the case analysis of a optimization problems found in managing a business, government, or non-profit organization, whether product or service oriented.

Assessment Criteria

1. In exams, there will be one major part for each chapter. In each part, one or more questions are asked.
Students are supposed to get at least 10 points from final exam so that he/she can be included in the bellcurve
calculations. If any exam question is left unanswered, the value of that question will be subtracted
from the exam score. If only the answer is given (i.e., no work showing how that answer was determined),
the question will be graded at 25% of its value.
2. Grade for Student Participation will depend on (i) your class attendance, (ii) the quality of the answers you
provide to questions posed by the instructor during class, and (iii) the general contribution you make to
the creation of a positive learning environment.
3. A good attendance record may bring the grade up one level, for grades on the boundary between two
grade levels.
4. The case analysis requires a cooperative effort. It is the responsibility of the team to assure that each
team member has contributed approximately equally to the group work. Cases will be graded by the
instructor and by the team members. Each member of the group will be asked at the end of the semester
to evaluate his or her own contribution, and those of other team members. A peer evaluation form will be
supplied during the last week of class.
5. Case reports will be evaluated for such factors as apparent understanding of the topic, originality of
treatment and discussion, accuracy of results, comprehensiveness of the report s content and depth of
the analysis, clarity and mechanics of presentation such as organization, format, punctuation, grammar,
and quality of exhibits and charts.

Language of Instruction

English

Course Policies and Rules

1. Attending at least 70 percent of lectures is mandatory.
2. Plagiarism of any type will result in disciplinary action.
3. Absence will not be considered an excuse for submitting homework assignments late.
4. Delayed case reports will suffer grade decay equivalent to one letter grade per day late.
5. Students are required to have their own calculator for this course. It will not be allowed to share a calculator
during exams. Cellular phones cannot be used as a calculator during an exam.

Contact Details for the Lecturer(s)

guzin.kavrukkoca@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 3 36
Preparations before/after weekly lectures 12 2 24
Preparation for midterm exam 1 16 16
Preparation for final exam 1 16 16
Preparing assignments 2 4 8
Preparing presentations 1 25 25
Final 1 1,5 2
Midterm 1 1,5 2
TOTAL WORKLOAD (hours) 129

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15
LO.111215222
LO.21314142
LO.311444143235
LO.411425145223
LO.511534134533