EM540 Nonlinear Programming

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

Information

Code EM540
Name Nonlinear Programming
Term 2023-2024 Academic Year
Semester . Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Doktora Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. ALİ KOKANGÜL


Course Goal / Objective

Mathematical modeling of the problems in real life, selection of the most suitable method for the modeled problem, solution derivation, transfer of the information necessary for the testing and implementation of the validity of the solution.

Course Content

Local and global optimization, Optimality conditions, Necessary and sufficient conditions for optimality, Unconstrained optimization, Constrained Optimization, Necessary and sufficient conditions for constrained optimization, Quadratic programming, Lagrangean methods, Convex analysis and convex programming, Multi-objective optimization methods, Computer implementation.

Course Precondition

The course has no prerequisites

Resources

Linear and Nonlinear Programming. Luenberger, D.G.; Ye Y. INTRODUCTION TO OPERATIONS RESEARCH, SEVENTH EDITION, Hillier/ Lieberman

Notes

Operations Research. Murthy, P.R.


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Improving analytical thinking ability
LO02 Model problems in real life
LO03 To be able to make sensitivity analysis
LO04 To be able to apply linear and nonlinear mathematical programming techniques to real problems.
LO05 To learn nonlinear mathematical modeling techniques
LO06 To gain the ability to use computer package programs used in the solution of mathematical modeling problems.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Conducts scientific research in industrial engineering, understands, interprets and applies knowledge in his/her field domain both in-depth and in-breadth. 5
PLO02 Bilgi - Kuramsal, Olgusal Keeps up with the recent changes and applications in the field of Industrial Engineering and examines and learns these innovations when necessary. 4
PLO03 Bilgi - Kuramsal, Olgusal Acquires detailed knowledge for methods and tools of industrial engineering and their limitations. 5
PLO04 Bilgi - Kuramsal, Olgusal Identifies, gathers and uses necessary information and data. 4
PLO05 Beceriler - Bilişsel, Uygulamalı Develops original definitions that will provide innovation to the field at the level of expertise for current and advanced information in the field based on graduate qualifications. 3
PLO06 Beceriler - Bilişsel, Uygulamalı Designs and performs analytical modeling and experimental research and analyze/solves complex matters emerged in this process. 5
PLO07 Beceriler - Bilişsel, Uygulamalı Has the ability to develop/propose new and/or original ideas and methods, propose new solutions for designing systems, components or processes. 1
PLO08 Beceriler - Bilişsel, Uygulamalı Designs Industrial Engineering problems, develops new methods to solve the problems and applies them. 4
PLO09 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Works in multi-disciplinary teams, take a leading role and responsibility and develop solutions for complex problems. 5
PLO10 Yetkinlikler - Öğrenme Yetkinliği Completes and applies the knowledge by using limited resources in scientific methods and integrates the knowledge in the field with the knowledge form various disciplines. 3
PLO11 Yetkinlikler - İletişim ve Sosyal Yetkinlik Uses a foreign language in verbal and written communication at least B2 level of European Language Portfolio.
PLO12 Yetkinlikler - İletişim ve Sosyal Yetkinlik Presents his/her research findings systematically and clearly in oral or written forms in national and international platforms. 4
PLO13 Yetkinlikler - İletişim ve Sosyal Yetkinlik Understands social and environmental implications of engineering practice. 1
PLO14 Yetkinlikler - Öğrenme Yetkinliği Considers social, scientific and ethical values in data collection, interpretation and announcement processes and professional activities. 4


Week Plan

Week Topic Preparation Methods
1 Local and global optimization Preliminary research on the subject and investigation of current applications Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
2 Optimality conditions Preliminary research on the subject and investigation of current applications Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
3 Necessary and sufficient conditions for optimality Preliminary research on the subject and investigation of current applications Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
4 Unconstrained optimization-I Preliminary research on the subject and investigation of current applications Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
5 Unconstrained optimization-II Preliminary research on the subject and investigation of current applications Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
6 Constrained Optimization-I Preliminary research on the subject and investigation of current applications Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
7 Constrained Optimization-II Preliminary research on the subject and investigation of current applications Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
8 Mid-Term Exam Preparation for the exam Ölçme Yöntemleri:
Yazılı Sınav
9 Necessary and sufficient conditions for constrained optimization Preliminary research on the subject and investigation of current applications Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
10 Quadratic programming Preliminary research on the subject and investigation of current applications Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
11 Lagrangian Methods lecture Preliminary research on the subject and investigation of current applications Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
12 Convex analysis and convex programming Preliminary research on the subject and investigation of current applications Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
13 Multi-objective optimization methods Preliminary research on the subject and investigation of current applications Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
14 Bilgisayar uygulamaları-I Preliminary research on the subject and investigation of current applications Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
15 Bilgisayar uygulamaları-II Preliminary research on the subject and investigation of current applications Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
16 Term Exams Preparation for the exam Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Preparation for the exam Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 5 70
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 15 15
Final Exam 1 30 30
Total Workload (Hour) 157
Total Workload / 25 (h) 6,28
ECTS 6 ECTS

Update Time: 12.05.2023 03:56