TYPE OF COURSE UNIT	Elective Course
LEVEL OF COURSE UNIT	Bachelor's Degree
YEAR OF STUDY	-
SEMESTER	-
NUMBER OF ECTS CREDITS ALLOCATED	5
NAME OF LECTURER(S)	Professor İmdat Kara
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) Understand the decision-making process 2) Understand the conditions for pareto-optimization 3) Evaluate and model the multi-criteria decisions 4) Have an ability to use modern solution approaches for multi-criteria decision problems 5) Learn the advantage of the softwares at the solution stage of the problems
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	Mathematics, especially Linear Algebra and Operations Research
COURSE DEFINITION	This course is one of the basic sections of Operations Research which studies the methods of decision making in real life situations when a choosing of the best alternative(s) among more than one due to the several criteria is necessary.The content of the course includes modeling and investigating the real life multi-criteria problems, evaluation and comparison methods for multi-criteria decisions, utility function theory and Analytic Hierarchy Process approaches, multi-objective optimization problems, order relations in vector spaces, various concepts of solutions in vector optimization, scalarization approaches for convex and nonconvex problems, and goal programming topics.
COURSE CONTENTS	WEEK TOPICS 1st Week Basic concepts. What is the decision making? Alternatives, Criteria. 2nd Week Decision variables and criteria spaces and transformations between them. 3rd Week Examples on multicriteria problems. Analytic Hierarchy Process (AHP) approaches in decision making. 4th Week Basic concepts of AHP, the consistency of comparison matrix, 5th Week Examples of Multi-Objective optimizatişon problems 6th Week Solution aproaches to the Multicriteria Decision Making 7th Week Scalarization of the objectives 8th Week Goal programming. Linear problems. Geometrical interpretation 9th Week Midterm 10th Week Preemptive goal programming models. 11th Week Aplications of the goal programming problems. 12th Week Concept of Pareto Optimality, Trade-of curves 13th Week Comprimise programming 14th Week Computer aplications.
RECOMENDED OR REQUIRED READING	Wayne L. Winston, Operations Research. Applications and Algorithms, Third edition, Duxbury Press, Belmont, California, 1994, Ronald R. Rardin (Purdue University), Optimization in Operations Research,Prentice-Hall, Inc., Upper Saddle River, New Jersey, 1998. Ders Notları
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Lecture,Problem Solving,Practice,Presentation
ASSESSMENT METHODS AND CRITERIA	Quantity Percentage(%) Mid-term 1 30 Assignment 1 20 Practice 1 15 Attendance 1 5 Total(%) 70 Contribution of In-term Studies to Overall Grade(%) 70 Contribution of Final Examination to Overall Grade(%) 30 Total(%) 100
ECTS WORKLOAD	Activities Number Hours Workload Midterm exam 1 2 2 Preparation for Quiz Individual or group work 14 2 28 Preparation for Final exam 1 25 25 Course hours 14 4 56 Preparation for Midterm exam 1 25 25 Laboratory (including preparation) Final exam 1 2 2 Homework 1 8 8 Total Workload 146 Total Workload / 30 4,86 ECTS Credits of the Course 5
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No