ECTSIntroduction to Optimization

Introduction to Optimization (MFGE412) Ders Detayları

Course Name Corse Code Dönemi Lecture Hours Uygulama Saati Lab Hours Credit ECTS
Introduction to Optimization MFGE412 Elective Courses 3 0 0 3 5
Pre-requisite Course(s)
MATH276, MATH380
Course Language İngilizce
Course Type Technical Elective Courses
Course Level Lisans
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Question and Answer, Drill and Practice.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives Implementation of optimization methods using MATLAB.
Course Learning Outcomes The students who succeeded in this course;
  • Understand optimization concepts in the solution of engineering problems (problem formulation, mathematical modeling, search and solution methods).
  • Gain skills in application of optimization tools in the analysis and solution of the engineering problems, implementation of optimization methods using MATLAB.
  • Improve skills on programming
  • Gain knowledge in optimization techniques and applications
Course Content Introduction to optimization, graphical optimization, least squares regression, linear and non-linear programming, numerical techniques, unconstrained and constrained optimization, global optimization (genetic algorithm), applications.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction to optimization. Chapters 13
2 Numerical Techniques Chapter 13
3 Graphical Optimization Chapter 15
4 Curve fitting (linear) Chapter 17
5 Curve fitting (linearizing) Chapter 17
6 Linear Programming Chapter 15
7 Linear Programming Chapter 15
8 Nonlinear Programming Chapter 14
9 Constrained Optimization Chapter 15
10 Genetic Algorithm Lecture notes
11 Genetic Algorithm Lecture notes
12 MATLAB Applications Chapter 15
13 Applications on Engineering Problems Chapter 16 and private study
14 Applications on Engineering Problems Chapter 16 and private study
15 Final exam period All chapters
16 Final exam period All chapters


Course Book 1. Numerical Methods for Engineers, S.C. Chapra & R.P. Canale, 5th Edition, McGraw-Hill, 2006
Other Sources 2. Applied Optimization with MATLAB Programming, Wiley, by P. Venkataraman (2002).
3. Practical Optimization (Algorithms and Engineering Applications), (Springer) by Antoniou, Andreas and Lu, Wu-Sheng (2007).
4. Numerical Optimization (Springer) by Jorge Nocedal and Stephen Wright (2006)
5. Practical Mathematical Optimization: An Introduction to Basic Optimization Theory and Classical and New Gradient-based Algorithms (Applied Optimization) by Jan A. Snyman (2005)

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation 1 5
Laboratory 5 25
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments - -
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 2 40
Final Exam/Final Jury 1 30
Toplam 9 100
Percentage of Semester Work 70
Percentage of Final Work 30
Total 100

Course Category

Core Courses
Major Area Courses X
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Accumulated knowledge on mathematics, science and mechatronics engineering; an ability to apply the theoretical and applied knowledge of mathematics, science and mechatronics engineering to model and analyze mechatronics engineering problems. X
2 An ability to differentiate, identify, formulate, and solve complex engineering problems; an ability to select and implement proper analysis, modeling and implementation techniques for the identified engineering problems. X
3 An ability to design a complex system, product, component or process to meet the requirements under realistic constraints and conditions; an ability to apply contemporary design methodologies; an ability to implement effective engineering creativity techniques in mechatronics engineering. (Realistic constraints and conditions may include economics, environment, sustainability, producibility, ethics, human health, social and political problems.) X
4 An ability to develop, select and use modern techniques, skills and tools for application of mechatronics engineering and robot technologies; an ability to use information and communications technologies effectively.
5 An ability to design experiments, perform experiments, collect and analyze data and assess the results for investigated problems on mechatronics engineering and robot technologies.
6 An ability to work effectively on single disciplinary and multi-disciplinary teams; an ability for individual work; ability to communicate and collaborate/cooperate effectively with other disciplines and scientific/engineering domains or working areas, ability to work with other disciplines.
7 An ability to express creative and original concepts and ideas effectively in Turkish and English language, oral and written, and technical drawings.
8 An ability to reach information on different subjects required by the wide spectrum of applications of mechatronics engineering, criticize, assess and improve the knowledge-base; consciousness on the necessity of improvement and sustainability as a result of life-long learning; monitoring the developments on science and technology; awareness on entrepreneurship, innovative and sustainable development and ability for continuous renovation.
9 Consciousness on professional and ethical responsibility, competency on improving professional consciousness and contributing to the improvement of profession itself.
10 A knowledge on the applications at business life such as project management, risk management and change management and competency on planning, managing and leadership activities on the development of capabilities of workers who are under his/her responsibility working around a project.
11 Knowledge about the global, societal and individual effects of mechatronics engineering applications on the human health, environment and security and cultural values and problems of the era; consciousness on these issues; awareness of legal results of engineering solutions.
12 Competency on defining, analyzing and surveying databases and other sources, proposing solutions based on research work and scientific results and communicate and publish numerical and conceptual solutions.
13 Consciousness on the environment and social responsibility, competencies on observation, improvement and modify and implementation of projects for the society and social relations and be an individual within the society in such a way that planing, improving or changing the norms with a criticism.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)
Laboratory 5 3 15
Special Course Internship
Field Work
Study Hours Out of Class 16 3 48
Presentation/Seminar Prepration
Homework Assignments 5 4 20
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 2 5 10
Prepration of Final Exams/Final Jury 1 5 5
Total Workload 98