Operations Research I

Course Code:

ISE 222

Course Period:

Spring

Course Type:

Core

Credits:

4

Theoric:

3

Practice:

0

Laboratory Hour:

2

ECTS:

9

Prerequisite Courses:

Linear Algebra

Introduction to Industrial Engineering

Course Language:

English

Courses given by:

Dilek Tüzün Aksu

Course Objectives:

This course aims to provide an introduction to the fundamental methods used in deterministic operations research with particular emphasis on modeling.

Course Content:

Topics covered include introduction to linear programming (LP) and its applications, sensitivity analysis, algebraic solution of an LP, duality theorem, network models and modeling of integer programming (IP) problems and branch-and-bound method for solving IPs. Applications of deterministic models in various settings as well as modeling and solution of LPs using commercial software will also be discussed.

Course Methodology:

1: Lecture, 2: Lab Exercises, 3: Project, 4: Problem Solving

Course Evaluation Methods:

A:Written Exam

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Course Learning Outcomes

Course Learning Outcomes	Detailed Program Outcomes	Teaching Methods	Assessment Methods
Builds linear programs for optimization problems in different settings.	2a, 6c	1, 2, 4	A
Solves linear programming models using graphical, algebraic and simplex methods.	1a,1b, 6c	1, 4	A
Makes sensitivity analysis and interpret results using the graphical method.	1a, 6c	1, 4	A
Defines the relationship between primal and dual problems, uses this relationship to obtain the optimal solution of linear programs and perform sensitivity analysis.	1a, 1b, 6c	1, 4	A
Identifies and models network flow problems that arise in different contexts such as transportation, assignment, maximum flow; solves these problems using problem specific methods.	2a, 2b, 6c	1, 2, 4	A
Models constraints and objective functions that can be formulated using integer variables.	2a, 6c	1, 2, 4	A
Can model linear and integer programming models using Excel Solver and Python and interpret the resulting outputs.	4a, 4b, 6c	1, 2	A

Course Flow

COURSE CONTENT
Week	Topics	Study Materials
1	INTRODUCTION TO MODELING (CHAPTER 1)	Textbook, Course Notes, CITGO Petrolium Article
2	GRAPHICAL SOLUTION OF A LINEAR PROGRAM (CHAPTER 3)	Textbook, Course Notes
3	LINEAR PROGRAMMING APPLICATIONS (CHAPTER 3)	Textbook, Course Notes
4	THE SIMPLEX ALGORITHM (CHAPTER 4)	Textbook, Course Notes
5	GOAL PROGRAMMING (CHAPTER 4)	Textbook, Course Notes
6	A GRAPHICAL APPROACH TO SENSITIVITY ANALYSIS (CHAPTER 6)	Textbook, Course Notes
7	ALGEBRA OF THE SIMPLEX METHOD (CHAPTER 6)	Textbook, Course Notes
8	ALGEBRA OF THE SIMPLEX METHOD (CHAPTER 6)	Textbook, Course Notes
9	DUAL THEOREM AND ITS CONSEQUENCES (CHAPTER 6)	Textbook, Course Notes
10	TRANSPORTATION, TRANSSHIPMENT AND ASSIGNMENT PROBLEMS (CHAPTER 7)	Textbook, Course Notes
11	SHORTEST PATH AND MAXIMUM FLOW PROBLEMS (CHAPTER 8)	Textbook, Course Notes
12	MINIMUM COST NETWORK FLOW AND MINIMUM SPANNING TREE PROBLEMS (CHAPTER 8)	Textbook, Course Notes
13	FORMULATION OF INTEGER PROGRAMMING PROBLEMS (CHAPTER 9)	Textbook, Course Notes
14	SOLUTION OF INTEGER PROGRAMMING PROBLEMS (CHAPTER 9)	Textbook, Course Notes

Recommended Sources

RECOMMENDED SOURCES
Textbook	OPERATIONS RESEARCH: APPLICATIONS AND ALGORITHMS, W. L. WINSTON, THOMPSON – BROOKS/COLE, 2004
Additional Resources

Material Sharing

MATERIAL SHARING
Documents	Modeling case study, CITGO Petrolium article, Python tutorial, lab notes, lecture notes
Assignments	Homeworks (1-3)
Exams	Midterm Exams (1-2), Final Exam

Assessment

ASSESSMENT
IN-TERM STUDIES	NUMBER	PERCENTAGE
Midterm 1	1	30
Midterm 2	1	25
Participation	1	10
Total		65
CONTRIBUTION OF FINAL EXAMINATION TO OVERALL GRADE		35
CONTRIBUTION OF IN-TERM STUDIES TO OVERALL GRADE		65
Total		100

Course’s Contribution to Program

COURSE'S CONTRIBUTION TO PROGRAM OUTCOMES
No	Program Learning Outcomes	check X
1a	Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline,	X
1b	Ability to use theoretical and applied knowledge in these areas in complex engineering problems.	X
2a	Ability to identify, formulate, and solve complex engineering problems,	X
2b	Ability to select and apply proper analysis and modeling methods for this purpose.	X
3a	Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result,
3b	Ability to apply modern design methods for this purpose.
4a	Ability to devise, select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice.	X
4b	Ability to employ information technologies effectively.	X
5a	Ability to design experiments for investigating complex engineering problems or discipline specific research questions,
5b	Ability to conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions.
6a	Ability to work efficiently in intra-disciplinary teams,
6b	Ability to work efficiently in multi-disciplinary teams,
6c	Ability to work individually.	X
7a	Ability to communicate effectively both orally and in writing,
7b	Knowledge of a minimum of one foreign language,
7c	Ability to write effective reports and comprehend written reports, prepare design and production reports,
7d	Ability to make effective presentations,
7e	Ability to give and receive clear and intelligible instructions.
8a	Recognition of the need for lifelong learning, ability to access information, ability to follow developments in science and technology,
8b	Ability to continue to educate him/herself.
9a	Consciousness to behave according to ethical principles and professional and ethical responsibility.
9b	Knowledge on standards used in engineering practice.
10a	Knowledge about business life practices such as project management, risk management, change management.
10b	Awareness in entrepreneurship and innovation.
10c	Knowledge about sustainable development.
11a	Knowledge about the global and social effects of engineering practices on health, environment, and safety,
11b	Knowledge about contemporary issues of the century reflected into the field of engineering.
11c	Awareness of the legal consequences of engineering solutions.

ECTS

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Course Duration	12	5	60
Hours for off-the-classroom study (Pre-study, practice)	14	5	70
Midterm examination	2	2	4
Homework	7	4	28
Project	1	50	50
Final examination	1	2	2
Total Work Load			214
Total Work Load / 25 (h)			8.6
ECTS Credit of the Course			9

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