| School/Faculty/Institute | Faculty of Engineering | ||||||
| Course Code | IE 202 | ||||||
| Course Title in English | Operations Research I | ||||||
| Course Title in Turkish | Yöneylem Araştırması I | ||||||
| Language of Instruction | EN | ||||||
| Type of Course | Flipped Classroom | ||||||
| Level of Course | Intermediate | ||||||
| Semester | Spring | ||||||
| Contact Hours per Week |
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| Estimated Student Workload | 160 hours per semester | ||||||
| Number of Credits | 6 ECTS | ||||||
| Grading Mode | Standard Letter Grade | ||||||
| Pre-requisites |
MATH 211 - Linear Algebra |
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| Co-requisites | None | ||||||
| Expected Prior Knowledge | Prior knowledge in matrix theory | ||||||
| Registration Restrictions | none | ||||||
| Overall Educational Objective | To learn deterministic operations research methodologies. | ||||||
| Course Description | This course introduces the most widely used deterministic operations research methodologies. The following topics are covered: introduction to operations research & linear programming (LP); model formulation; graphical solution procedure; selected LP applications; Simplex method; big-M method; two phase method; special cases in Simplex method; matrix representation of the Simplex method; graphical sensitivity analysis; dual problem; duality theorems; complementary slackness theorem; economic interpretation of duality; dual Simplex method; post optimality analysis; transportation problem; assignment problem. |
Course Learning Outcomes and CompetencesUpon successful completion of the course, the learner is expected to be able to:1) formulate linear programming models; 2) solve and analyze linear programming problems; 3) comprehend the basics and usage of Simplex algorithm; 4) explain the relation between primal and dual solutions and give the economic interpretation of dual solutions; 5) follow solution techniques for specialized linear programming problems such as transportation and assignment problems; 6) function effectively as a member of a team; 7) use OR software to solve mathematical models. |
| Program Learning Outcomes/Course Learning Outcomes | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
|---|---|---|---|---|---|---|---|
| 1) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics | |||||||
| 2) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors | |||||||
| 3) An ability to communicate effectively with a range of audiences | |||||||
| 4) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts | |||||||
| 5) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives | |||||||
| 6) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions | |||||||
| 7) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies |
| N None | S Supportive | H Highly Related |
| Program Outcomes and Competences | Level | Assessed by | |
| 1) | An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics | H | Exam,Participation,Project |
| 2) | An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors | N | |
| 3) | An ability to communicate effectively with a range of audiences | N | |
| 4) | An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts | N | |
| 5) | An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives | S | Project |
| 6) | An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions | S | Exam,Participation,Project |
| 7) | An ability to acquire and apply new knowledge as needed, using appropriate learning strategies | N |
| Prepared by and Date | HANDE KÜÇÜKAYDIN , March 2024 |
| Course Coordinator | HANDE KÜÇÜKAYDIN |
| Semester | Spring |
| Name of Instructor | Asst. Prof. Dr. HANDE KÜÇÜKAYDIN |
| Week | Subject |
| 1) | Introduction to Operations Research (OR) & Linear Programming (LP) Modeling; |
| 2) | Graphical LP Solution & Model Formulation; |
| 3) | Selected LP Applications & Introduction to Simplex Method; |
| 4) | Simplex Method; |
| 5) | Simplex Method, Starting Methods; |
| 6) | Starting Methods, Sensitivity Analysis; |
| 7) | Sensitivity Analysis; |
| 8) | Matrix Representation of the Simplex Method; |
| 9) | Duality; |
| 10) | Duality & Dual Simplex Method; |
| 11) | Post-Optimal Analysis; |
| 12) | Post-Optimal Analysis, Transportation Problem; |
| 13) | Transportation Problem; |
| 14) | Assignment Problem; |
| 15) | Final Exam/Project/Presentation Period; |
| 16) | Final Exam/Project/Presentation Period. |
| Required/Recommended Readings | • Taha, H. A. (2017). Operations Research: An Introduction (10th Edition). Upper Saddle River, New Jersey: Pearson • Winston, W.L. (2003). Operations Research: Applications and Algorithms (4th Edition). Cengage Learning | ||||||||||||||||||
| Teaching Methods | Lectures/contact hours using “flipped classroom” as an active learning technique | ||||||||||||||||||
| Homework and Projects | 1 mini-project regarding the use of a linear programming solver | ||||||||||||||||||
| Laboratory Work | none | ||||||||||||||||||
| Computer Use | GAMS | ||||||||||||||||||
| Other Activities | |||||||||||||||||||
| Assessment Methods |
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| Course Administration |
hande.kucukaydin@mef.edu.tr +902123953631 Instructor’s -office and phone number: 5th floor, 212 3953631 -office hours: TBA -email address: hande.kucukaydin@mef.edu.tr Exams and quizzes: Closed book and closed notes. Rules for attendance: YÖK regulations. You are responsible for the announcements made in class. Rules for late submission of assignments: N/A Missing a quiz: Provided that proper documents of excuse are presented, a make-up exam will be given for each missed quiz. Missing a project: Project deadlines are always late for (0,24] hours receive 70% of the credit they get, (24,48] hours receive 35% , and (48,72] receive 10%. Missing a midterm: You are expected to be present without exception and to plan any travel around these dates accordingly. Medical emergencies are of course excluded if accompanied by a doctor’s note. A note indicating that you were seen at the health center on the day of the exam is not a sufficient documentation of medically excused absence from the exam. The note must say that you were medically unable to take the exam. Provided that proper documents of excuse are presented, a make-up exam will be given for each missed midterm. If you fail to take the exam on the assigned day and do not have a valid excuse, you will be given zero (0) on the exam. Employment interviews, employer events, weddings, vacations, etc. are not excused absences. Eligibility to take the final exam: YÖK regulations. Missing a final: Faculty regulations. A reminder of proper classroom behavior, code of student conduct: YÖK Regulations Statement on plagiarism: YÖK Regulations (http://3fcampus.mef.edu.tr/uploads/cms/webadmin.mef.edu.tr/4833_2.pdf) extendable up to 72 hours, with submissions |
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| Activity | No/Weeks | Hours | Calculation | ||||
| No/Weeks per Semester | Preparing for the Activity | Spent in the Activity Itself | Completing the Activity Requirements | ||||
| Course Hours | 14 | 1 | 3 | 1 | 70 | ||
| Project | 1 | 1 | 5 | 20 | 26 | ||
| Quiz(zes) | 3 | 4 | 1 | 15 | |||
| Midterm(s) | 1 | 20 | 2 | 22 | |||
| Final Examination | 1 | 25 | 2 | 27 | |||
| Total Workload | 160 | ||||||
| Total Workload/25 | 6.4 | ||||||
| ECTS | 6 | ||||||