Poisson and renewal processes; discrete and continuous Markov chains; applications in queuing, reliability, inventory, production, and telecommunication problems; introduction to queuing networks and network performance analysis.
Stochastic Processes (IE 503)
2022 Fall
Faculty of Engineering and Natural Sciences
Industrial Engineering(IE)
3
10.00
Ahmet Barış Balcıoğlu -balcioglu@sabanciuniv.edu,
English
Doctoral, Master
--
Formal lecture
Other
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| Programs\Type | Required | Core Elective | Area Elective |
| MA-European Studies | |||
| MA-European Studies-Non Thesis | |||
| MA-Political Science | |||
| MA-Political Science-Non Thes | |||
| MA-Visual Arts&Vis. Com Des-NT | |||
| MA-Visual Arts&Visual Com Des | |||
| MS-Bio. Sci. & Bioeng. LFI | |||
| MS-Bio. Sci. & Bioeng. LFI-ENG | |||
| MS-Biological Sci&Bioeng. | * | ||
| MS-Business Analytics | |||
| MS-Computer Sci.&Eng. LFI | |||
| MS-Computer Sci.&Eng. LFI-ENG | |||
| MS-Computer Science and Eng. | * | ||
| MS-Cyber Security(with thesis) | * | ||
| MS-Data Science | |||
| MS-Elec. Eng&Comp Sc.LFI-ENG | |||
| MS-Electronics Eng&Comp Sc.LFI | |||
| MS-Electronics Eng&Computer Sc | * | ||
| MS-Electronics Eng. | * | ||
| MS-Electronics Eng. LFI | |||
| MS-Electronics Eng. LFI-ENG | |||
| MS-Energy Techno.&Man. | * | ||
| MS-Industrial Eng. LFI-ENG | |||
| MS-Industrial Engineering | * | ||
| MS-Industrial Engineering LFI | |||
| MS-Manufacturing Eng-Non Thes | * | ||
| MS-Manufacturing Engineering | * | ||
| MS-Materials Sci & Engineering | * | ||
| MS-Materials Sci. & Eng. LFI | |||
| MS-Materials Sci.&Eng. LFI-ENG | |||
| MS-Mathematics | |||
| MS-Mechatronics | * | ||
| MS-Mechatronics LFI | |||
| MS-Mechatronics LFI-ENG | |||
| MS-Physics | |||
| MS-Physics-Non Thesis | * | ||
| MS-Psychology | |||
| MS-Psychology-Non Thesis | |||
| PHD-Biological Sci&Bioeng. | * | ||
| PHD-Comp. Sci and Eng.after UG | * | ||
| PHD-Computer Science and Eng. | * | ||
| PHD-Cyber Security | * | ||
| PHD-Electronics Eng&ComputerSc | * | ||
| PHD-Electronics Eng. | * | ||
| PHD-Electronics Eng. after UG | * | ||
| PHD-Experimental Psychology | |||
| PHD-Industrial Engineering | * | ||
| PHD-Management | |||
| PHD-Manufacturing Eng after UG | * | ||
| PHD-Manufacturing Engineering | * | ||
| PHD-Materials Sci.&Engineering | * | ||
| PHD-Mathematics | |||
| PHD-Mechatronics | * | ||
| PHD-Mechatronics after UG | * | ||
| PHD-Physics | |||
| PHD-Physics after UG | |||
| PHD-Social Psychology | |||
| PHDBIO after UG | * | ||
| PHDCYSEC after UG | * | ||
| PHDEECS after UG | * | ||
| PHDEPSY after UG | |||
| PHDIE after UG | * | ||
| PHDMAN after UG | |||
| PHDMAN after UG-Finance | |||
| PHDMAN after UG-Man. and Org. | |||
| PHDMAN after UG-Op.&Sup. Cha. | |||
| PHDMAN-Finance Area | |||
| PHDMAN-Man. and Org. Area | |||
| PHDMAN-Op. & Supp. Chain Area | |||
| PHDMAT after UG | * | ||
| PHDMATH after UG | |||
| PHDSPSY after UG |
CONTENT
OBJECTIVE
In this course, we will review the fundamental concepts of the theory of probability and learn about a variety of stochastic processes and we will also discuss some of their applications in engineering. The main objective of this course is to enable students to ?think probabilistically,? and to develop and analyze probability models that capture the effects of randomness on systems under consideration.
LEARNING OUTCOME
The student will be able to model stochastic phenomena in real life (when it applies) as a discrete time or a continuous time Markov chain.
The student will be able to analyze, present, and criticize academic papers involving stochastic processes, queueing models, Markov chains.
The student will link how the probability theory can be employed to model and analyze systems that evolve randomly over time.
The student will learn how a customer arrival process can be modeled as a Poisson process.
Update Date:
ASSESSMENT METHODS and CRITERIA
| Percentage (%) | |
| Final | 30 |
| Midterm | 70 |
RECOMENDED or REQUIRED READINGS
| Textbook |
Introduction to Probability Models, Sheldon M. Ross, 9th Edition, 2006, |