DECISION ANALYSIS

IND414

Course Code: IND414
Semester: -
Theory+Practice: 3 + 1
ECTS: 5

Course Type

Elective Course

Course Level

Bachelor's Degree

Year of Study

Semester

ECTS

Name of Lecturer(s)

Learning Outcomes

At the end of this course, the students;

Understand the decision-making process
Understand the conditions for pareto-optimization
Evaluate and model the multi-criteria decisions
Have an ability to use modern solution approaches for multi-criteria decision problems
Learn the advantage of the softwares at the solution stage of the problems

Mode of Delivery

Face to face

Prerequisites

Recommended Optional Programme Components

Mathematics, especially Linear Algebra and Operations Research

Course Description

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
1^st Week	Basic concepts. What is the decision making? Alternatives, Criteria.
2^nd Week	Decision variables and criteria spaces and transformations between them.
3^rd Week	Examples on multicriteria problems. Analytic Hierarchy Process (AHP) approaches in decision making.
4^th Week	Basic concepts of AHP, the consistency of comparison matrix,
5^th Week	Examples of Multi-Objective optimizatişon problems
6^th Week	Solution aproaches to the Multicriteria Decision Making
7^th Week	Scalarization of the objectives
8^th Week	Goal programming. Linear problems. Geometrical interpretation
9^th Week	Midterm
10^th Week	Preemptive goal programming models.
11^th Week	Aplications of the goal programming problems.
12^th Week	Concept of Pareto Optimality, Trade-of curves
13^th Week	Comprimise programming
14^th Week	Computer aplications.

Recommended 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

Language of Instruction

Turkish

Work Placement(s)

Programme Qualifications / Learning Outcomes

	LO1	LO2	LO3	LO4	LO5
K1		X
K2	X		X
K3
K4				X	X
K5					X
K6
K7
K8
K9
K10
K11