IE 313 • Tüm Sınavlar • Operations Research III
Sabancı Üniversitesi IE 313 (Operations Research III) Midterm I sınavına hazırlık paketi.
İşlenen konular: Discrete Time Markov Chains, Limiting Distributions and State Classifications, Long Term Properties of Markov Chains, Absorbing Markov Chains, Python Implementation of Markov Chains, Poisson Processes.
Ayda 1333 TL, peşin fiyatına 3 taksit
Eğitmen
Ömer Faruk Altun
Co-founder & Head of Education
2011 yılında Endüstri Mühendisliği okumak için başladığım Sabancı Üniversitesi'nden 2018 yılında Bilgisayar Mühendisi olarak mezun oldum. 13 yıldır Altun ismiyle başta Sabancı Üniversitesi olmak üzere çeşitli okullarda Endüstri ve Bilgisayar Mühendisliği alanlarında ders vermekteyim. Unicourse'ta sunduğum derslerin yanında eğitim departmanının da sorumluluğunu üstlenmekteyim.
Konular
Probability Review
4 konu anlatımı
Random Variables and Probability Distributions
Conditional Probability
Total Probability Rule
Expected Value
Discrete Time Markov Chains
8 konu anlatımı
What is a Markov Chain?
One-Step Transition Probabilities
Example
n-Step Transition Probabilities
Chapman-Kolmogorov Equations
Example
Unconditional State Probabilities
Example
Limiting Distributions and State Classifications
7 konu anlatımı
Steady State Distribution
Example
Classes and State Properties
Periodicity and Ergodic Markov Chains
Example
Example
Example
Long Term Properties of Markov Chains
5 konu anlatımı
First Passage Times
Example
Expected First Passage Time
Expected Recurrence Time
Example
Absorbing Markov Chains
9 konu anlatımı
Absorbing Markov Chains
Matrix Structure
Inverse of a Matrix
Expected Number of State Visits
Example
Expected Time Until Absoption
Example
Absorption Probabilities
Example
Python Implementation of Markov Chains
4 konu anlatımı
DTMC Simulation 1
DTMC Simulation 2
DTMC Simulation 3
Coding Absorbing MC
Poisson Processes
13 konu anlatımı
Counting Processes
Assumptions of Poisson Processes
Example 1
Memoryless Property
Example 2
Minimum of Exponential Random Variables
Example 3
Thinning
Example 4
Superposition
Example 5
Non-homogenous Poisson Processes
Example 6
Sample Exam Problems
22 soru
Discrete Time Markov Chains 1
Discrete Time Markov Chains 2
Discrete Time Markov Chains 3
Discrete Time Markov Chains 4
Limiting Distribution and State Classifications 1
Limiting Distribution and State Classifications 2
Limiting Distribution and State Classifications 3
Limiting Distribution and State Classifications 4
Limiting Distribution and State Classifications 5
Limiting Distribution and State Classifications 6
Long Term Properties of Markov Chains 1
Long Term Properties of Markov Chains 2
Absorbing Markov Chains 1
Absorbing Markov Chains 2
Python Implementation 1
Python Implementation 2
Python Implementation 3
Poisson Processes 1
Poisson Processes 2
Poisson Processes 3
Poisson Processes 4
Poisson Processes 5
🦄 🦄 Fall 2024 Midterm I Exam 🦄 🦄
5 soru
Limiting Distribution and State Classifications
Python Implementation
Limiting Distribution and Long-Term Properties
Absorbing Markov Chains
Poisson Processes
🦄 🦄 Spring 2025 Midterm I Exam 🦄 🦄
4 soru
State Classifications
Absorbing Chains
Limiting Distributions
Poisson Processes
🦄 🦄 Fall 2025 Midterm I Exam 🦄 🦄
5 soru
State Classifications
Markov Chains + Python
Limiting Distributions
Absorbing Chains
Poisson Processes
Genel bir tekrar!
12 soru
Markov Chains
Markov Chains
Markov Chains
State Classifications
State Classifications
Limiting Distributions
Limiting Distributions
Limiting Distributions
Long Term Properties of Markov Chains
Absorbing Chains
Poisson Processes
Poisson Processes
Tekrar edilmesi gereken Poisson soruları!!!
5 soru
Poisson Processes
Poisson Processes
Poisson Processes
Poisson Processes
Poisson Processes
Continuous Time Markov Chains
18 konu anlatımı
From Discrete to Continuous
Example 1
Example 2
Example 3
Steady State Distribution
Q Matrix
Example 4
Example 5
Example 6
Absorbing Chains
Example 7
Embedded Chains
Example 8
Embedded Chains and Stationary Distribution
Example 9
Example 10
Time Reversibility
Example 11
Birth-Death Models
11 konu anlatımı
A subproblem of CTMC
Random Rates, Finite Chain
Example 1
Random Rates, Infinite Chain
Example 2
Equal Rates, Infinite Chain, Single Server
Example 3
Equal Rates, Finite Chain, Single Server
Example 4
Equal Rates, Finite Chain, Multiple Servers
Example 5
Sample Midterm II Problems
9 soru
Continuous Time Markov Chains 1
Continuous Time Markov Chains 2
Continuous Time Markov Chains 3
Continuous Time Markov Chains 4
Continuous Time Markov Chains 5
Birth and Death 1
Birth and Death 2
Birth and Death 3
Birth and Death 4
🦄 🦄 Fall 2024 Midterm II Exam 🦄 🦄
6 soru
Continuous Time Markov Chains 1
Continuous Time Markov Chains 2
Birth-and-Death 1
Continuous Time Markov Chains 3
Birth-and-Death 2
Her Başlık Uygun Buraya
🦄 🦄 Fall 2025 Midterm II Exam 🦄 🦄
5 soru
Poisson Processes
Poisson Processes
Continuous Time Markov Chains
Continuous Time Markov Chains
Birth-Death Processes
🦄 🦄 Spring 2025 Midterm II Exam 🦄 🦄
4 soru
Poisson Processes
Continuous Time Markov Chains
Continuous Time Markov Chains
Birth-Death Processes
Queueing Theory
10 konu anlatımı
Kendall's Notation
Terminology
M/M/1 Queue
Example 1
M/M/s Queue
Example 2
M/M/1/K Queue
Example 3
M/M/s/K Queue
Example 4
Python Implementation of Queueing Theory
5 konu anlatımı
Coding for Markovian Queues
M/M/1/K Queue
M/M/1 Queue
M/M/s/K Queue
M/M/s Queue
Sample Exam Problems
8 soru
Queueing Theory 1
Queueing Theory 2
Queueing Theory 3
Queueing Theory 4
Queueing Theory 5
Queueing Theory 6
Queueing Theory 7
Queueing Theory 8
🦄 🦄 Fall 2024 Final Exam 🦄 🦄
7 soru
Discrete Time Markov Chains 1
Continuous Time Markov Chains 1
Discrete Time Markov Chains 2
Poisson Processes
Continuous Time Markov Chains 2
Queueing Theory 1
Queueing Theory 2
🦄 🦄 Fall 2025 Final Exam 🦄 🦄
8 soru
Continuous Time Markov Chains
Poisson Process
Discrete Time Markov Chains
Birth-Death Processes
Queueing Models + Python
True/False 1
True/False 2
True/False 3