COURSE UNIT TITLE

: MULTIOBJECTIVE AND MULTICRITERIA PROGRAMMING

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IND 5018 MULTIOBJECTIVE AND MULTICRITERIA PROGRAMMING ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR ADIL BAYKASOĞLU

Offered to

INDUSTRIAL ENGINEERING (ENGLISH)
Industrial Engineering - Thesis (English) (Evening Program)
INDUSTRIAL ENGINEERING (ENGLISH)
INDUSTRIAL ENGINEERING - NON THESIS (ENGLISH)
INDUSTRIAL ENGINEERING - NON THESIS (EVENING PROGRAM) (ENGLISH)

Course Objective

The main objective of this course is to teach decision making models will be based multi-criteria and multi-objective emphasize will be given on the relevance of these models to a practical situation as well as theoretical properties under appropriate sets of assumptions. This course will teach basics of MCDM and MOO. It will discuss and introduce several MCDM-MOO techniques like AHP,TOPSIS, ELECTRE, ANP, PROMETHEE, FCM, GRA, Pareto Optimality, Utility Methods etc. Applications of these methods to practical problems will also be presented.

Learning Outcomes of the Course Unit

1   Ability to model multiple criteria problems
2   Ability to apply necessary methods to solve multi criteria problems
3   Ability to analyze results
4   Ability to apply results

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to MCDM-MOO
2 Introduction to basic methods-1
3 Introduction to basic methods-2
4 TOPSIS and VIKOR techniques with applications
5 ELECTRE and PROMETHEE techniques with applications
6 AHP and ANP techniques with applications
7 ELECTRE and FCM approaches for interaction analyses in MCDM
8 Group Decision Making
9 MOO concepts, problem formulation and Pareto Optimality
10 MOO concepts, problem formulation and Pareto Optimality
11 MOO techniques with applications-1
12 MOO techniques with applications-2
13 Case Study
14 Case Study

Recomended or Required Reading

Saaty, T., Multicriteria Decision Making: The Analytic Hierarchy Process, RWS Pub., 1990
K . Paul Yoon, Ching-Lai Hwang,"Multiple Attribute Decision Making: An Introduction " Sage Publications,1995, ISBN: 0803954867

Planned Learning Activities and Teaching Methods

Class presentations, case studies and practical applications

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.25 + ASG *0.25 +FIN *0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.25 + ASG *0.25 +RST *0.50


Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Prof.Dr. Adil Baykasoğlu
+90 232 301 76 00

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 7 98
Preparation for midterm exam 1 15 15
Preparation for final exam 1 20 20
Preparing presentations 1 25 25
Midterm 1 3 3
Final 1 3 3
TOTAL WORKLOAD (hours) 206

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.1343334344
LO.2434343
LO.333333443
LO.44344334

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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