EASTERN MEDITERRANEAN UNIVERSITY
Department of Industrial Engineering
IENG313 Operations Research I
COURSE OUTLINE
Course Code
IENG313
Course Level
Third year
Course Title
Operations Research I
Course Type
Department Core
Credit Value
(4, 1, 0) 4
ECTS Value
6
Pre-requisites
IENG212, MATH241
Co-requisites
-
Prepared by
Sayman Demirciler (Date: September 2011)
Semester and Year
Fall 2011-2012
Course Web Link :
http://ie.emu.edu.tr/lec/lecturer.php?lec=Nirmal+Kambo&course=ieng313
Course Schedule : Tuesday: 12:30-14:30; Thursday: 12:30-14-30; Friday: 12:30-13:30 ; Office Hour: Tuesday 11:00-12:00
Instructor
Assistant(s)
Name (group)
Sayman Demirciler
Nima Mirzaei
Mazyar Ghadirinejad
e-mail
Sayman.demirciler@emu.edu.tr
nima.mirzaei@emu.edu.tr
Mazyar.nejad@cc.emu.edu.tr
Office
B – 103
C - 205
B - 208
Telephone
1441
1587
1592
COURSE DESCRIPTION
This course is designed to introduce the fundamentals of operations research. The emphasis is on solution of deterministic optimization
models. The topics covered are application of scientific methodology to business problems, systems concept, team concept in problem
analysis, and mathematical modeling. Basic deterministic methods used in the course are linear programming, simplex method, duality,
dual simplex method, post-optimality analysis, integer programming, formulation, branch and bound techniques, cutting plane algorithm
and maximal flow algorithm, non-linear programming, unconstrained nonlinear optimization and Lagrange multiplier method .
AIMS & OBJECTIVES
The purpose of this course is to introduce the students to the application of scientific methods to complex decision-making problems in
engineering and business problems. This includes,
1. How to model real-life problems,
2. Bringing attention to the complexity of the problems,
3. Teaching of solution algorithms,
4. How to evaluate solutions and apply to decision making.
COURSE LEARNING OUTCOMES
On successful completion of this course, all students will have developed knowledge and understanding of:

Modeling real life problems, (1)

Mathematical aspect of basic feasible solutions,(3)

Elements of Simplex Method and its variations,(2), (3)

Methods of finding solution to problems involving linear models with continuous and integer variables,(3)

Sensitivity of optimum solution of a model to possible changes in values of uncontrollable parameters,(4)

Solving Linear Programming and Integer Programming problems using LINGO,(5)

Modelling and solving network problems,(1),(3)

Solving unconstrained non-linear Programming Problems,(3)
On successful completion of this course, all students will have developed their skills in:

Building models of real life systems,1),(3)

Finding solutions to linear and integer linear models, (3)

Performing post-optimality analysis to facilitate the smooth application of theoretical results to the actual problem,(4)

Finding solutions to unconstrained non linear objective function,(3)
On successful completion of this course, all students will have developed their appreciation of, and respect for values and attitudes to:

Role of linear models in industrial engineering,(1)

Importance of modelling and optimization in diverse field of science and engineering,(1),(2)

Impact of optimization software in solving models for real-life situation,(5)

Systems approach to problem solving,(1),(3)
CONTRIBUTION TO PROFESSIONAL PROGRAM COMPONENTS
This course contributes to engineering and mathematical topics through creative modelling applications.
CONTRIBUTION OF THE COURSE TO PROGRAM EDUCATIONAL OBJECTIVES AND OUTCOMES:
The course helps to achieve the following program educational objectives:

develop skills in critical thinking, teamwork, problem solving and communicating with others

ability to perform research to enlarge the boundaries of their knowledge
The course makes significant contributions to the following program outcomes:
 an ability to apply knowledge of mathematics, science, and engineering
 an ability to design and conduct experiments, as well as to analyze and interpret data
 an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic,
environmental, social, political, ethical, health and safety, manufacturability, and sustainability
 an ability to identify, formulate, and solve engineering problems
 an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice.
TEXTBOOK/S
Winston , Wayne L., “Operations Research : Applications and Algorithms” 4th edition, Duxbury Press 2004.
REFERENCES (available at EMU Library)
 Taha Hamdy A, “Operations Research”, 7th international edition, Prentice Hall 2003.
 Hillier, F.S.; Lieberman , G.J., “Introduction to Operations Research”, 9th international edition, McGraw Hill 2009.
METHOD OF ASSESSMENT
All Examinations will be based on lectures, discussions, textbook and assigned work. To enter a formal examination, a student has to
present her/his EMU student Identification card to the invigilator.
Quizzes: There will be several quizzes designed to test familiarity and basic understanding of various topics. There will be no quiz makeups.
Midterm Exams: The midterm exam I will be held in the week designated by the university administration. It will cover all of the material
up to the date of examination.
Final Exam: The final exam will cover the whole course material. In form it will be a longer version of the midterm exam.
Make-up Exams: Make-up examinations will only be offered to students who provided adequate documentation for the reason of their
absence within four working days at the latest after the examination date. One final exam type make-up exam will be offered after the final
exams for the missed midterm and/or final exam. University regulations apply for graduate make-ups.
Any objection to the grade or mark should be made latest within a week following its announcement.
Grading Policy:
Class Participation
Quizzes
Midterm Exam
Case study & Lab
Final Exam
5%
20 %
25 %
20 %
30%
COURSE CONTENT (WEEKLY TEACHING PLAN)
Week
1-2
2-4
5-6
7-8
9-10
11-12
13-14
Date
Topics
Introduction to OR, Formulation of LP problem
Graphical Solution, Simplex Algorithms, Special Cases
Duality, Dual Simplex method and Sensitivity Analysis
Transportation, Assignment and Transshipment Problems
Simple Network, Minimal Spanning Tree Algorithm, Dijkstra’s Algorithm and Maximal Flow Algorithm
Integer Programming, Branch and Bound Algorithm, Cutting Plane Algorithm
Nonlinear Programming, Unconstrained Optimization and Langrange Multiplier Method
LEARNING/TEACHING METHODS
This is a basic course which prepares the students for several allied courses in the future. Teaching will enable the students to understand
the techniques of OR and problem formulation. To get a hands on experience, lectures will be suppliemented by tutorials and lab sessions.
ATTENDANCE
Attendance will be taken every lecture hour. Note that university regulations allow the instructor to give a grade of NG to a student whose
absenteeism is more than 25% of the total lecture hours or who do not complete sufficient work.
ACADEMIC HONESTY - PLAGIARISM
Cheating is copying from others or providing information, written or oral, to others. Plagiarism is copying without acknowledgement from
other people’s work. According to university by laws cheating and plagiarism are serious offences punishable with disciplinary action
ranging from simple failure from the exam or project, to more serious action (letter of official warning suspension from the University for
up to One Semester). Disciplinary action is written in student records and may appear in student transcripts.
PLEASE KEEP THIS COURSE OUTLINE FOR FUTURE REFERENCE AS IT CONTAINS IMPORTANT INFORMATION