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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS IND 5017 DYNAMIC AND STOCHASTIC 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

PROFESSOR DOCTOR BILGE BILGEN

Offered to

INDUSTRIAL ENGINEERING (ENGLISH) Industrial Engineering - Thesis (English) (Evening Program) INDUSTRIAL ENGINEERING (ENGLISH) INDUSTRIAL ENGINEERING - NON THESIS (ENGLISH) INDUSTRIAL ENGINEERING - NON THESIS (EVENING PROGRAM) (ENGLISH)

Course Objective

This course aims to give a good insight into the fundamental ideas of dynamic programming and stochastic systems and a good working knowledge of the relevant techniques with emphasis on applications in manufacturing and production planning.

Learning Outcomes of the Course Unit

1   Ability to model dynamic systems 2   Ability to solve manufacturing and production planning problems using dynamic programming

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Unconstrained Optimization - Functions of One Variable 2 Functions of Several Variables 3 Constrained Optimization 4 Introduction To Probability Theory 5 Random Variables, Expectations & Independence 6 Bernoulli and Poisson Processes 7 Markov Chains and Processes 8 Mid-term exam 9 Introduction To Dynamic Programming - Basic Theory and Computations 10 Deterministic Dynamic Programming - One Dimensional Dynamic Programming 11 Multi Dimensional Dynamic Programming 12 Stochastic Dimensional Dynamic Programming - Finite Stage Systems, Infinite Stage Systems 13 Student presentations 14 Student presentations

Recomended or Required Reading

Cooper, L. & Cooper M.W., "Introduction To Dynamic Programming", Pergamon Press., 1981

Planned Learning Activities and Teaching Methods

The course consists of lectures and class discussions

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 ASG ASSIGNMENT 3 FIN FINAL EXAM 4 FCG FINAL COURSE GRADE MTE * 0.25 + ASG *0.25 +FIN *0.50 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.25 + ASG *0.25 +RST *0.50

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Prof.Dr. Adil Baykasoglu, Phone: 0232 3017600

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 3 39 Preparations before/after weekly lectures 13 7 91 Preparation for midterm exam 1 20 20 Preparation for final exam 1 25 25 Preparing presentations 1 20 20 Final 1 3 3 Midterm 1 3 3 TOTAL WORKLOAD (hours) 201

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 LO.1 3 2 1 5 5 4 4 3 4 LO.2 3 5 4 4 5 2 5 3 4