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Course Description Course Name : Multi Objective Optimization Course Code : IEM 759 Course Type : Optional Level of Course : Second Cycle Year of Study : 1 Course Semester : Fall (16 Weeks) ECTS : 6 Name of Lecturer(s) : Asst.Prof.Dr. SEMİN PAKSOY Learning Outcomes of the Course : Gains the ability to perform the multiobjective decision making techniques Gains the ability to perform the multiattribute desicion making techniques Formulates complex systems by performing the optimization techniques Gains the ability to structure and analyse problems Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : The course provides the students with the ability to perform the optimization techniques for constrained, unconstrained and multipleobjective optimization problems by reinforcing optimization concepts and condititions. Course Contents : The course covers introduction to optimization, nonlinear optimization, necessary and sufficient conditions, constrained optimization methods: Gradient Method(Steepest decent method) and Newton´s method, unconstrained optimization methods, exterior - interior penalties, multiple objective optimization and their methods. Language of Instruction : Turkish Work Place : Classroom   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Optimization and conditions Reading relevant parts in the source books according to weekly program Lecture, problem solving 2 Unconstrained optimization Reading relevant parts in the source books according to weekly program Lecture, problem solving 3 Constrained optimization Reading relevant parts in the source books according to weekly program Lecture, problem solving 4 Basic concepts and definition Reading relevant parts in the source books according to weekly program Lecture, problem solving 5 Creating models and structure of model (Dominance, efficiency and optimality relations) Reading relevant parts in the source books according to weekly program Lecture, problem solving 6 The use of graphical method Reading relevant parts in the source books according to weekly program Lecture, problem solving 7 Multiobjective simplex method Reading relevant parts in the source books according to weekly program Lecture, problem solving 8 Midterm exam - - 9 Multiobjective decision making techniques Reading relevant parts in the source books according to weekly program Lecture, problem solving 10 Conflicting objectives Reading relevant parts in the source books according to weekly program Lecture, problem solving 11 Application with the worksheet Reading relevant parts in the source books according to weekly program Lecture, problem solving 12 Goal programming Reading relevant parts in the source books according to weekly program Lecture, problem solving 13 Goal programming solving techniques Reading relevant parts in the source books according to weekly program Lecture, problem solving 14 Sensitivity analysis (Structural changes) Reading relevant parts in the source books according to weekly program Lecture, problem solving 15 Sensitivity analysis (Coefficient changes) Reading relevant parts in the source books according to weekly program Lecture, problem solving 16/17 Final exam - -   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Multiobjective Optimisation and Control, G. P. Liu, J. B. Yang and J. F. Whidborne, RESEARCH STUDIES PRESS LTD. Baldock, Hertfordshire, England    An Introduction to Management Science: Quantitive Approaches to Decisions Making, David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Thomson, 2003 Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 60     Homeworks/Projects/Others 10 40 Total 100 Rate of Semester/Year Assessments to Success 40   Final Assessments 100 Rate of Final Assessments to Success 60 Total 100   Contribution of the Course to Key Learning Outcomes # Key Learning Outcome Contribution* 1 Explains Econometric concepts 4 2 Equipped with the foundations of Economics, develops Economic models 2 3 Models problems using the knowledge of Mathematics, Statistics, and Econometrics 5 4 Acquires the ability to analyze, benchmark, evaluate and interpret at conceptual levels to develop solutions to problems 5 5 Collects, edits, and analyzes data 5 6 Uses advanced software packages concerning Econometrics, Statistics, and Operation Research 4 7 Develops the ability to use different resources in an area which has not been studied in the scope of academic rules, synthesizes the information gathered, and gives effective presentations 3 8 Speaks Turkish and at least one other foreign language in accordance with the requirements of academic and business life. 3 9 Questions traditional approaches and their implementation and develops alternative study programs when required 3 10 Recognizes and implements social, scientific, and professional ethic values 3 11 Gives a consistent estimate for the model and analyzes and interprets its results 5 12 Takes responsibility individually and/or as a member of a team; leads a team and works effectively 1 13 Defines the concepts of statistics, operations research and mathematics. 4 14 Knowing the necessity of life-long learning, follows the latest developments in the field of study and improves himself continiously 4 15 Follows the current issues, and interprets the data about economic and social events. 3 16 Understands and interprets the feelings, thoughts and behaviours of people and expresses himself/herself orally and in written form efficiently 1 * Contribution levels are between 0 (not) and 5 (maximum).   Student Workload - ECTS Works Number Time (Hour) Total Workload (Hour) Course Related Works     Class Time (Exam weeks are excluded) 14 3 42     Out of Class Study (Preliminary Work, Practice) 14 4 56 Assesment Related Works     Homeworks, Projects, Others 10 3 30     Mid-term Exams (Written, Oral, etc.) 1 10 10     Final Exam 1 10 10 Total Workload: 148 Total Workload / 25 (h): 5.92 ECTS Credit: 6