COURSE UNIT TITLE

: LOCATION THEORY

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IND 5046 LOCATION THEORY 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

ASSOCIATE PROFESSOR MUALLA GONCA AVCI

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 aim of this course is to introduce the fundamental location models as well as their extensions. Moreover, students will get familiar to exact and heuristic solution approaches for location problems.

Learning Outcomes of the Course Unit

1   Ability to describe main concepts of location models
2   Ability to classify location problems
3   Ability to model real-life location problems
4   Ability to solve location problems
5   Ability to use software applications for solving location problems

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction and classification of location problems
2 Review of linear programming
3 An overview of complexity theory
4 Covering problems
5 Center problems
6 Median problems
7 Fixed charge facility location problems
8 Lagrangian relaxation method
9 Heuristic algorithms
10 Benders decomposition method
11 Extensions of location models
12 Student presentations

Recomended or Required Reading

Textbooks:

Daskin, Mark S. Network and discrete location: models, algorithms, and applications. John Wiley & Sons, 2011.

Laporte, Gilbert, Stefan Nickel, and Francisco Saldanha da Gama, eds. Location science. Vol. 528. Berlin: Springer, 2015.

Supplementary Book(s):

Farahani, Reza Zanjirani, and Masoud Hekmatfar, eds. Facility location: concepts, models, algorithms and case studies. Springer Science & Business Media, 2009.

Eiselt, Horst A., and Vladimir Marianov, eds. Foundations of location analysis. Vol. 155. Springer Science & Business Media, 2011.

Planned Learning Activities and Teaching Methods

Course notes given on board or visual presentations, in-class debates, assignments, student presentations, software 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 * 0.30 +ASG * 0.20 +FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + ASG * 0.20 + 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)

gonca.yunusoglu@deu.edu.tr

Office Hours

To be announced

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
0
Preparations before/after weekly lectures 13 6 78
Preparation for midterm exam 1 20 20
Preparation for final exam 1 25 25
Preparing assignments 1 25 25
Preparing presentations 1 10 10
0
Midterm 1 2 2
Final 1 2 2
TOTAL WORKLOAD (hours) 201

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.1434333
LO.24343
LO.344355
LO.444355
LO.545355