COURSE UNIT TITLE

: INTRODUCTION TO COMPUTATIONAL INTELLIGENCE

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IND 4919 INTRODUCTION TO COMPUTATIONAL INTELLIGENCE ELECTIVE 3 0 0 4

Offered By

Industrial Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ŞENER AKPINAR

Offered to

Industrial Engineering

Course Objective

The aim of this course is to introduce metaheuristic algorithms, which are software computing techniques, and to gain the ability to solve optimization problems with these algorithms.

Learning Outcomes of the Course Unit

1   To have a basic level of knowledge about metaheuristic algorithms.
2   To have the knowledge of which arrangements metaheuristic algorithms require in order to be used in solving optimization problems.
3   Ability to adapt Genetic Algorithm, Ant Colony Optimization and Simulated Annealing Algorithms for solving optimization problems.
4   Ability to code Genetic Algorithm, Ant Colony Optimization and Simulated Annealing Algorithms for solving optimization problems using MATLAB.
5   Ability to adapt and code metaheuristic algorithms for solving optimization problems.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Programming with MATLAB
2 Programming with MATLAB
3 Programming with MATLAB
4 Metaheuristic Algorithms
5 Metaheuristic Algorithms
6 Genetic Algorithm
7 Genetic Algorithm
8 Ant Colony Optimization
9 Ant Colony Optimization
10 Simulated Annealing Algorithms
11 Simulated Annealing Algorithms
12 Project Presentations
13 Project Presentations
14 Project Presentations

Recomended or Required Reading

Glover, F. W., & Kochenberger, G. A. (Eds.). (2006). Handbook of metaheuristics (Vol. 57). Springer Science & Business Media.
Talbi, E. G. (2009). Metaheuristics: from design to implementation. John Wiley & Sons.
Siarry, P. (Ed.). (2016). Metaheuristics. Cham, Switzerland: Springer International Publishing.
Shah, P., Sekhar, R., Kulkarni, A. J., & Siarry, P. (Eds.). (2021). Metaheuristic algorithms in industry 4.0. CRC Press.

Planned Learning Activities and Teaching Methods

The presentations which are prepared by using books, articles and proceedings as well as class board will be used in the scope of the course programme.

Assessment Methods

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


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

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)

Professor Adil BAYKASOĞLU, Phd.
adil.baykasoglu@deu.edu.tr

Office Hours

Afternoon at the thursday and friday

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 2 28
Preparation for midterm exam 1 5 5
Preparation for final exam 1 7 7
Preparing presentations 5 2 10
Final 1 1,5 2
Midterm 1 1,5 2
TOTAL WORKLOAD (hours) 96

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.15
LO.25
LO.355
LO.455
LO.55

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

Copyright 2015 DEÜ. BİD

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