COURSE INFORMATION FORM

Faculty Faculty of Engineering Program B.Sc. in Electrical-Electronics Engineering Elective

B.Sc. in Industrial Engineering Required B.Sc. in Computer Engineering Elective B.Sc. in Mechanical Engineering Elective B.Sc. in Civil Engineering Elective

Semester Fall 2016-2017

Course Code IE 301 Course Title in English

Operations Research II

Course Title in Turkish

Yöneylem Araştırması II

Language of Instruction

English

Type of Course Flipped Classroom Level of Course Undergraduate Course Category (by % of Content)

Basic Science Basic Engineering Engineering Design General Education 20 80 - -

Semester Offered Fall Contact Hours per Week

Lecture: 3 hours Recitation: - Lab:- Other: (Office hours)

Estimated Student Workload

143 hours per semester.

Number of Credits 6 ECTS Grading Mode Standard Letter Grade Pre-requisites MATH 221

Expected Prior Knowledge

Basic probability knowledge

Co-requisites None Registration Restrictions

Only Undergraduate Students

Overall Educational Objective

To learn stochastic operations research methodologies.

Course Description This course introduces the students to stochastic models and methodologies for analyzing and providing solutions to decision-making problems with uncertainties. The course will emphasize Markov Chains, Exponential Distribution, Poisson Process and Queuing Theory, and their applications in real life problems.

Course Description in Turkish Bu dersin belirsizlik altında karar verme problemlerinde kullanılmak üzere rassal metot ve

yöntemleri öğrencilere tanıtır. Bu ders Markov Zincirleri, Üssel Dağılım, Poisson Süreçleri, ve Kuyruk Teorisi konularını ve bunların uygulamarını içerecektir.

Course Learning Outcomes and Competences

Upon successful completion of the course, the learner is expected to be able to: 1. show the ability to construct stochastic models of the problems that arise in random environments using Markov Chains, 2. construct models using Poisson Process, 3. perform performance evaluation using Queuing Theory.

Relation to Student Outcomes and Competences: N=None S=Supportive H=Highly Related Relationship of the Course with the Student Outcomes and Competences Level Assessed by N/S/H

(Related Learning Outcomes)

Exam, Project, HW, Lab, Presentation, etc.

(a) an ability to apply knowledge of mathematics, science, and engineering H

(1,2,3)

Exams, Quizzes

(b) an ability to design and conduct experiments, as well as to analyze and interpret data

N

(c) 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

S

Exams, Quizzes

(d) an ability to function on multidisciplinary teams

N

(e) an ability to identify, formulate, and solve engineering problems

H

(1,2,3)

Exams, Quizzes

(f) an understanding of professional and ethical responsibility

N

(g) an ability to communicate effectively S

Flipped Classroom Practice, Active Learning Activities

(h) the broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context

N

(i) a recognition of the need for, and an ability to engage in life-long learning S

Flipped Classroom Practice, Active Learning Activities

(j) a knowledge of contemporary issues

N

(k) an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice

S

Exams, Quizzes

Prepared by and date Assoc. Prof. Semra Ağralı / October 2016 Name of Instructors Assoc. Prof. Semra Ağralı Course Contents Week Topic 1. Review of Basic Probability 2. Introduction to Stochastic Processes – Markov Chains 3. Illustrative examples of Markov Chain Applications 4. Steady State Probabilities and Applications 5. Absorbing Markov Chains and Their Analysis 6. Application of Markov Chains & Problem Sessions 7. Exponential Distribution (ED) and Poisson Processes (PP) I 8. Exponential Distribution (ED) and Poisson Processes (PP) II 9. Application of ED and PP 10. Introduction to Queuing Theory – Terminology 11. Birth-Death Processes 12. M/M/1/GD/∞/∞, M/M/1/GD/c/∞, 13. M/M/s/GD/∞/∞, M/M/s/GD/c/∞, 14. Application of QS 15. Final Period

16. Final Period Required/Recommended Readings

• Taha, H. A., Operations Research: An Introduction (9th Edition). Upper Saddle River, New Jersey: Pearson.

• Ross, S.M., Introduction to Probability Models (8th Edition). Academic Press, Elsevier. • Winston, W. L., Operations Research – Applications and Algorithms. Brooks/Cole

CENGAGE Learning, Belmont, Canada. Teaching Methods Lectures/contact hours using “flipped classroom” as an active learning technique Homework and Projects - Laboratory Work - Computer Use - Other Activities - Assessment Methods Types of assessment:

Number Ratio (%) Midterm Exam 1 35 Quizzes Best 5 out of plenty quizzes 25 (each contributing 5%) Final Exam 1 40 Total 100

Course Administration Instructor’s office and phone number: 5th Floor office hours: Tuesdays 9:40-10:20 & 12:40-13:20 email address: agralis@mef.edu.tr The best way to contact me is via email. However if discussing the subject over email is not possible or answering your question via email is complicated, I reserve the right to request that you attend office hours. I reserve the right to request students attend office hours when stopping by my office during non-office hour time periods. FOLLOWING RULES ARE NON NEGOTIABLE! Attendance: You are responsible for the announcements made in class. (Also, you may miss some of the quizzes if you do not attend class regularly.) Exam/Quiz Grading Appeals: Every effort will be made to ensure that grading is as objective and fair as possible. If you believe that there is an error in the grading, please submit, in writing, an appeal within one week of your exam grade being announced. However, please be advised that if you submit such an appeal, the entire exam will be regraded to ensure that all parts are properly graded. As such, your grade on the exam could increase or decrease based on the secondary grading. Missing a quiz: No make-up will be given since five best of the quizzes will be included in the total grade. 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 the day of the exam is not sufficient documentation of a medically excused absence from an exam. The note must say that you were medically unable to take the exam. Provided that proper documents of excuse are presented, missed midterm by the student will be given the grade of the final exam. No make-up will be given. If you fail to take the exam on the assigned day and do not have a valid excuse, you will be given a zero (0) on the exam. Employment interviews, employer events, weddings, vacations, etc. are not excused absences. Missing a final: Faculty regulations. Eligibility to enter the final exam: Students are required to achieve 25% success rate as the average of the midterm exam and quizzes in order to enter the final exam. 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 ) Disclaimer: The instructor reserves the right, when necessary, to alter the grading policy, change examination dates, and modify the syllabus and course content. Modifications will be announced in class. Students are responsible for the announced changes.

ECTS Student Workload Estimation

Activity No/Weeks Calculation Explanation

No/Weeks per Semester (A)

Preparing for the Activity (B)

Spent in the Activity Itself (C)

Completing the Activity

Requirements (D)

Lecture/Flipped Classroom 14 1 3 1.5 77 A*(B+C+D)

Quizzes 5 3 0.5 17.5 A*(B+C+D)

Midterm(s) 1 20 1.5 21.5 A*(B+C+D)

Final Examination 1 25 2 27 A*(B+C+D)

Total Workload 143

Total Workload/25 5.72

ECTS 6

Hours

PROGRAM CRITERIA

1. Breadth in industrial engineering practice, analysis and design with 17 required course in industrial engineering, and depth in one or more fields with 4 industrial engineering electives.

2. Ability to design, develop, implement and improve integrated systems that include people, materials, information, equipment, and energy.

3. In-depth knowledge of appropriate analytical, experimental and computational methods for system integration.

Key verbs for cognitive domain in writing learning outcomes and competences:

Key Verbs: Remembering: defines, describes, identifies, knows, labels, lists, matches, names, outlines, recalls, recognizes, reproduces, selects, states. Understanding: comprehends, converts, defends, distinguishes, estimates, explains, extends, generalizes, gives an example, infers, interprets, paraphrases, predicts, rewrites, summarizes, translates. Applying: applies, changes, computes, constructs, demonstrates, discovers, manipulates, modifies, operates, predicts, prepares, produces, relates, shows, solves, uses. Analyzing: analyzes, breaks down, compares, contrasts, diagrams, deconstructs, differentiates, discriminates, distinguishes, identifies, illustrates, infers, outlines, relates, selects, separates. Evaluating: appraises, compares, concludes, contrasts, criticizes, critiques, defends, describes, discriminates, evaluates, explains, interprets, justifies, relates, summarizes, supports. Creating: categorizes, combines, compiles, composes, creates, devises, designs, explains, generates, modifies, organizes, plans, rearranges, reconstructs, relates, reorganizes, revises, rewrites, summarizes, tells, writes. Key verbs for affective domain in writing learning outcomes and competences: Receiving Phenomena: asks, chooses, describes, follows, gives, holds, identifies, locates, names, points to, selects, sits, erects, replies, uses. Responding to Phenomena: answers, assists, aids, complies, conforms, discusses, greets, helps, labels, performs, practices, presents, reads, recites, reports, selects, tells, writes. Valuing: completes, demonstrates, differentiates, explains, follows, forms, initiates, invites, joins, justifies, proposes, reads, reports, selects, shares, studies, works. Organizing: adheres, alters, arranges, combines, compares, completes, defends, explains, formulates, generalizes, identifies, integrates, modifies, orders, organizes, prepares, relates, synthesizes. Internalizing values: acts, discriminates, displays, influences, listens, modifies, performs, practices, proposes, qualifies, questions, revises, serves, solves, verifies.