COURSE UNIT TITLE

: DYNAMIC PROGRAMMING

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
STA 6051 DYNAMIC PROGRAMMING ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR UMAY ZEYNEP UZUNOĞLU KOÇER

Offered to

Statistics
Statistics
STATISTICS

Course Objective

This is a course on the theory and practice of deterministic and stochastic dynamic programming. At the conclusion of this course the student will have learned the art of formulating recursive equations, and how and why dynamic programming is the only method that can solve many of the large scale optimization problems involving sequential decision making.

Learning Outcomes of the Course Unit

1   Defining basic concepts on sequential decision making and Markovian decision process
2   Expressing the deterministic or stochastic large scale optimization problems by dynamic programming frame
3   Formulating recursive relations
4   Analyzing the problems on Markov decision or semi-Markov decision process
5   Making suggestions on sequential decision making problems so that the system work more efficient
6   Reviewing the related literature and present examples

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to sequential decision making, basic concepts, finite decision trees
2 Dynamic programming networks and the principle of optimality
3 Formulation of recursive relations, the shortest path problem
4 Applications: critical path method, resource allocation, knapsack problem
5 Applications: Production problem, capacity expanding, equipment replacement problems
6 Infinite decision trees
7 Infinite Horizon Optimization including Equipment Replacement over an Unbounded Horizon
8 MIDTERM
9 Stochastic dynamic programming, examples, stochastic shortest path problem, inventory control problem, Presentation
10 Markov decision process, Presentation
11 Markov decision process
12 Examples of Markov decision process, Homework
13 Semi- Markov decision process, Homework
14 Semi- Markov decision process

Recomended or Required Reading

Textbook(s):
E.V. Denardo, 2003, "Dynamic Programming- Models and Applications", Dover Publications,NY.

References:
S.M. Ross, 1983, "Introduction to Stochastic Dynamic Programming", Academic Press, USA.

Materials: None

Planned Learning Activities and Teaching Methods

Lecture, problem solving, homework, presentation

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 PRS PRESENTATION
4 FIN FINAL EXAM
5 FCG FINAL COURSE GRADE MTE* 0.30 + ASG * 0.20 + PRS * 0.10 + FIN * 0.40
6 RST RESIT
7 FCGR FINAL COURSE GRADE (RESIT) MTE* 0.30 + ASG * 0.20 + PRS * 0.10 + RST * 0.40


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of midterm, presentation, homework, and final exam.

Language of Instruction

English

Course Policies and Rules

Student responsibilities:
Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy.

Contact Details for the Lecturer(s)

DEU Fen Fakültesi Istatistik Bölümü
e-mail: umay.uzunoglu@deu.edu.tr
Tel: 0232 301 85 60

Office Hours

It will be announced when the course schedule of the faculty is determined.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparing assignments 2 20 40
Preparing presentations 2 20 40
Preparation for midterm exam 1 10 10
Preparation for final exam 1 15 15
Preparations before/after weekly lectures 14 4 56
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 207

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.15
LO.2544444
LO.3544
LO.4544545
LO.555455
LO.65445554

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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