Information Package / Course Catalogue
IE 301 Operations Research II
MEF University
Degree Programs
Psychology
General Information For Students
Diploma SupplementErasmus Policy Statement
Psychology
Bachelor Length of the Programme: 4 Number of Credits: 240 TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF: Level 6

Ders Genel Tanıtım Bilgileri

School/Faculty/Institute Faculty of Engineering
Course Code IE 301
Course Title in English Operations Research II
Course Title in Turkish Yöneylem Araştırması II
Language of Instruction EN
Type of Course Flipped Classroom,Lecture
Level of Course Introductory
Semester Fall
Contact Hours per Week
Lecture: 3 Recitation: none Lab: none Other: none
Estimated Student Workload 148 hours per semester
Number of Credits 6 ECTS
Grading Mode Standard Letter Grade
Pre-requisites MATH 227 - Probability and Statistics for Engineering I
Expected Prior Knowledge Basic probability knowledge
Co-requisites None
Registration Restrictions none
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, Queuing Theory and Markov Decision Process, 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, Kuyruk Teorisi ve Markov Karar Süreçleri konularını ve bunların uygulamalarını 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;
4) evaluate different strategies using Markov Decision Process.
5) applies stochastic modeling and queuing theory techniques on some real life cases
6) analyzes, compares alternative stochastic optimization techniques and designs a solution method to stochastic optimization problems
Program Learning Outcomes/Course Learning Outcomes 1 2 3 4 5 6
1) Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology.
2) Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation.
3) Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes.
4) Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts.
5) Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline.
6) Internalization and dissemination of professional ethical standards.
7) Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences.
8) Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level).
9) Recognition, understanding, and respect for the complexity of sociocultural and international diversity.
10) Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement.
11) Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses.
12) Ability to acquire knowledge independently, and to plan one’s own learning.
13) Demonstration of advanced competence in the clarity and composition of written work and presentations.

Relation to Program Outcomes and Competences

N None S Supportive H Highly Related
     
Program Outcomes and Competences Level Assessed by
1) Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. N
2) Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. N
3) Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. H Exam,HW,Participation
4) Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. N
5) Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. N
6) Internalization and dissemination of professional ethical standards. N
7) Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences. N
8) Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level). N
9) Recognition, understanding, and respect for the complexity of sociocultural and international diversity. S Participation
10) Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. S HW,Participation
11) Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. N
12) Ability to acquire knowledge independently, and to plan one’s own learning. S Exam,HW
13) Demonstration of advanced competence in the clarity and composition of written work and presentations. H Exam,HW
Prepared by and Date EVREN GÜNEY , December 2023
Course Coordinator FİLİZ GÜRTUNA
Semester Fall
Name of Instructor Asst. Prof. Dr. FİLİZ GÜRTUNA

Course Contents

Week Subject
1) Introduction to Stochastic Processes – Markov Chains
2) Illustrative examples of Markov Chain Applications
3) Steady State Probabilities and Applications
4) Absorbing Markov Chains and Their Analysis (Quiz 1)
5) Application of Markov Chains
6) Exponential Distribution (ED) and Poisson Processes (PP) I
7) Exponential Distribution (ED) and Poisson Processes (PP) II
8) Introduction to Queuing Theory – Terminology
9) M/M/1/GD/N/ type of Queuing Systems (Midterm)
10) M/M/1/GD/N type of Queuing Systems
11) Application of Queuing Systems
12) Markov Decision Process I
13) Markov Decision Process II
14) Markov Decision Process III
15) Final examination / presentation period
16) Final examination / presentation period
Required/Recommended ReadingsTextbook: Taha, H. A., Operations Research: An Introduction (9th Edition). Upper Saddle River, New Jersey: Pearson. Supplementary: (1) Ross, S.M., Introduction to Probability Models (8th Edition). Academic Press, Elsevier. (2) Winston, W. L., Operations Research – Applications and Algorithms. Brooks/Cole CENGAGE Learning, Belmont, Canada.
Teaching MethodsLectures/contact hours using “flipped classroom” as an active learning technique
Homework and Projects• Problems from textbook (they will not be collected and not graded, quiz questions will be very similar or identical to the problems). • A term project that covers all topics learned in this course
Laboratory Worknone
Computer UseExcel use is strongly recommended
Other Activitiesnone
Assessment Methods
Assessment Tools Count Weight
Quiz(zes) 1 % 30
Midterm(s) 1 % 30
Final Examination 1 % 40
TOTAL % 100
Course Administration guneye@mef.edu.tr
212 3953740
Instructor’s -office and phone number: 5th floor, 212 3953740 -office hours: TBA -email address: semra.agrali@mef.edu.tr Exams and quizzes: Closed book and closed notes. Homework: N/A 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: No make-up will be given for the missed quizzes. For certain excuses (decided by the instructor) the percentage of the missed quiz may be added to the midterm or to the final. 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, 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 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 Academic dishonesty and plagiarism: YÖK Regulations

ECTS Student Workload Estimation

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 2 84
Homework Assignments 5 1.5 0.5 10
Quiz(zes) 5 1.5 0.5 10
Midterm(s) 1 20 2 22
Final Examination 1 25 2 27
Total Workload 153
Total Workload/25 6.1
ECTS 6