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 |