ISB105 Network Optimization

3 ECTS - 2-0 Duration (T+A)- 1. Semester- 2 National Credit

Information

Code ISB105
Name Network Optimization
Term 2024-2025 Academic Year
Semester 1. Semester
Duration (T+A) 2-0 (T-A) (17 Week)
ECTS 3 ECTS
National Credit 2 National Credit
Teaching Language Türkçe
Level Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Doç. Dr. NİMET ÖZBAY
Course Instructor Doç. Dr. NİMET ÖZBAY (A Group) (Ins. in Charge)


Course Goal / Objective

The aim of this course is to teach the basics and techniques of network optimization, to develop the ability to use solution approaches and algorithms for various network problems

Course Content

The content of this course consists of the topics of Introduction to Network Theory, Minimum Spanning Tree Problems, Shortest Path Problems, Maximum Flow Problems, Minimum-cost Flow Problems, Matching and Covering, Euler Graph and Postman Problems, Travelling Salesman Problems

Course Precondition

None

Resources

-Şebeke Optimizasyonu, Prof.Dr. Cevriye Gencer, Dr. Yunus Emre Karamanoğlu, Nobel Akademik Yayıncılık, 2020, 342s. -Yöneylem Araştırması, Prof.Dr. Ahmet Öztürk, Ekin Basım Yayın, 2016, 894s. -Yöneylem Araştırması, Hamdy A. Taha, Literatür Yayıncılık, 2003.

Notes

-İşletmede Sayısal Yöntemler ve Winqsb Uygulamaları, Prof.Dr. İsmail Erdem, Seçkin Yayıncılık, 2017, 535s.


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Explains network theory
LO02 Applies solution algorithms for minimum spanning tree problems
LO03 Uses Prim's algorithm, Kruskal's algorithm and Boruvka's algorithm
LO04 Applies solution algorithms for shortest path problems
LO05 Uses Bellman equation, Dijkstra's algorithm and Floyd–Warshall algorithm
LO06 Uses maximum flow problems and solution methods
LO07 Solves minimum-cost flow problems
LO08 Explains Euler graph and postman problems and the algorithms used to solve them
LO09 Applies the types of travelling salesman problems and solution algorithms


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Explain the essence fundamentals and concepts in the field of Statistics
PLO02 Bilgi - Kuramsal, Olgusal Emphasize the importance of Statistics in life 4
PLO03 Bilgi - Kuramsal, Olgusal Define basic principles and concepts in the field of Law and Economics
PLO04 Bilgi - Kuramsal, Olgusal Produce numeric and statistical solutions in order to overcome the problems
PLO05 Bilgi - Kuramsal, Olgusal Use proper methods and techniques to gather and/or to arrange the data 2
PLO06 Bilgi - Kuramsal, Olgusal Utilize computer programs and builds models, solves problems, does analyses and comments about problems concerning randomization
PLO07 Bilgi - Kuramsal, Olgusal Apply the statistical analyze methods 3
PLO08 Bilgi - Kuramsal, Olgusal Make statistical inference (estimation, hypothesis tests etc.)
PLO09 Bilgi - Kuramsal, Olgusal Generate solutions for the problems in other disciplines by using statistical techniques and gain insight
PLO10 Bilgi - Kuramsal, Olgusal Discover the visual, database and web programming techniques and posses the ability of writing programs
PLO11 Beceriler - Bilişsel, Uygulamalı Distinguish the difference between the statistical methods
PLO12 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Make oral and visual presentation for the results of statistical methods 2
PLO13 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Have capability on effective and productive work in a group and individually
PLO14 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs
PLO15 Yetkinlikler - Öğrenme Yetkinliği Develop scientific and ethical values in the fields of statistics-and scientific data collection


Week Plan

Week Topic Preparation Methods
1 Introduction to Network Theory Source reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
2 Minimum Spanning Tree Problems Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap
3 Prim's Algorithm, Kruskal's Algorithm and Boruvka's Algorithm Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Problem Çözme
4 Shortest Path Problems Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap
5 Bellman Equation, Dijkstra's Algorithm and Floyd–Warshall Algorithm Source reading Öğretim Yöntemleri:
Anlatım, Bireysel Çalışma, Problem Çözme
6 Maximum Flow Problems Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap
7 Ford-Fulkerson Algorithm Source reading Öğretim Yöntemleri:
Anlatım, Problem Çözme
8 Mid-Term Exam Ölçme Yöntemleri:
Yazılı Sınav
9 Minimum-cost Flow Problems Source reading Öğretim Yöntemleri:
Anlatım
10 Matching and Covering Source reading Öğretim Yöntemleri:
Anlatım
11 Euler Graph Problems and Solution Algorithms Source reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama, Problem Çözme
12 Types of Postman Problems and Solution Methods Source reading Öğretim Yöntemleri:
Anlatım, Problem Çözme
13 Travelling Salesman Problems by Network Types Source reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
14 Various Algorithms for Solving Travelling Salesman Problems Source reading Öğretim Yöntemleri:
Alıştırma ve Uygulama, Problem Çözme, Anlatım
15 Solving Problems Source reading Öğretim Yöntemleri:
Bireysel Çalışma, Problem Çözme
16 Term Exams Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 2 28
Out of Class Study (Preliminary Work, Practice) 14 2 28
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 6 6
Final Exam 1 16 16
Total Workload (Hour) 78
Total Workload / 25 (h) 3,12
ECTS 3 ECTS

Update Time: 12.06.2024 05:25