COURSE SYLLABUS

DYNAMIC PROGRAMMING

1	Course Title:	DYNAMIC PROGRAMMING
2	Course Code:	EKO6120
3	Type of Course:	Optional
4	Level of Course:	Third Cycle
5	Year of Study:	1
6	Semester:	2
7	ECTS Credits Allocated:	4
8	Theoretical (hour/week):	2
9	Practice (hour/week) :	0
10	Laboratory (hour/week) :	0
11	Prerequisites:	None
12	Recommended optional programme components:	None
13	Language:	Turkish
14	Mode of Delivery:	Face to face
15	Course Coordinator:	Dr. ESMA BİRİŞÇİ
16	Course Lecturers:	Dr. Öğr. Üyesi Esma Birişçi
17	Contactinformation of the Course Coordinator:	esmabirisci@uludag.edu.tr Telefon:0224 2941016 Bursa Uludağ Üniversitesi İİBF A blok
18	Website:
19	Objective of the Course:	The aim of this section is to develop an understanding of the theory of dynamic programming and to discuss different research areas such as revenue management, healthcare, revenue management, production planning, warehouse control and maintenance. The focus of the course will be on the theory as well as applications of the Dynamic Programming technique to different research areas. This course is a basic introduction to the theory of Dynamic Programming and some applications.
20	Contribution of the Course to Professional Development	Within the scope of the course, students develop analytical thinking and problem-solving skills by understanding nonlinear and dynamic programming techniques in complex problems. In addition, they gain advantage in risk management and strategic decision-making processes by learning advanced methods for modeling uncertainty and solving stochastic problems. These gains enable students to have strong technical competencies and versatile expertise in the business world by expanding their application knowledge in different areas such as inventory management, pricing, production and revenue management.

Learning Outcomes:

1	Understand the main ideas of nonlinear and dynamic programming techniques in deterministic problems ;
2	Model the uncertainty inherent in real-world dynamic problems by formulating finite and infinite horizon stochastic dynamic problems.;
3	Apply backward induction, value iteration, and policy iteration to solve finite and infinite horizon problems and formulate dynamic programs as linear programs;
4	Ability to apply different types of dynamic programming in different application areas, such as inventory control, pricing, production, and revenue management;

22	Course Content:

Week	Theoretical	Practical
1	Introduction to the main ideas of nonlinear programming and the role of dynamic programming in nonlinear optimization.
2	Shortest path problem. Optimality principle. Examples
3	Controlled Markov chains. Finite horizon stochastic problems Dynamic programming equations.
4	Dynamic programming equations. Applications
5	Discounted infinite horizon problems
6	Value and policy iteration methods. Linear programming approach
7	Applications in inventory control, planning and logistics
8	Multi-armed bandit problem
9	Undiscounted infinite horizon problems. Stochastic shortest paths
10	Methods for solving undiscounted problems
11	Optimal stopping; asset pricing
12	Average cost problems
13	Methods for solving average cost problems
14	Introduction to approximate dynamic programming. TD(?). Addition. Q-learning. Examples.

23	Textbooks, References and/or Other Materials:	Ross, Sheldon M. Applied Probability Models with Optimization Applications, Dover books, 1992. Puterman, Martin L., Markov Decision Processes, Wiley, 2008.
24	Assesment

TERM LEARNING ACTIVITIES	NUMBER	PERCENT
Midterm Exam	1	20
Quiz	3	20
Homeworks, Performances	3	20
Final Exam	1	40
Total	8	100
Contribution of Term (Year) Learning Activities to Success Grade		60
Contribution of Final Exam to Success Grade		40
Total		100
Measurement and Evaluation Techniques Used in the Course	Written and practice questions.
Information	The Quiz given during the term affects the final grade.

ECTS / WORK LOAD TABLE

Activites	NUMBER	TIME [Hour]	Total WorkLoad [Hour]
Theoretical	14	2	28
Practicals/Labs	0	0	0
Self Study and Preparation	0	0	0
Homeworks, Performances	3	20	60
Projects	1	10	10
Field Studies	0	0	0
Midtermexams	1	10	10
Others	0	0	0
Final Exams	1	10	10
Total WorkLoad			118
Total workload/ 30 hr			3,93
ECTS Credit of the Course			4

CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS

	PQ1	PQ2	PQ3	PQ4	PQ5	PQ6	PQ7	PQ8	PQ9	PQ10	PQ11	PQ12
LO1	4	5	5	4	4	5	5	5	4	4	5	5
LO2	4	3	4	5	4	5	5	5	4	5	4	5
LO3	4	5	5	5	5	5	5	5	5	5	5	5
LO4	5	5	4	4	4	3	3	4	4	4	4	3

LO: Learning Objectives

PQ: Program Qualifications

Contribution Level:

1 Very Low

2 Low

3 Medium

4 High

5 Very High