COURSE UNIT TITLE

: COMPUTATIONAL LOGISTICS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IND 5058 COMPUTATIONAL LOGISTICS 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 DERYA EREN AKYOL

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

This course will present the fundamental quantitative approaches that are used in the design and control of logistics systems, including modeling issues, design concepts, computational considerations particularly in city distribution, and the use of the MATLAB software package.

Learning Outcomes of the Course Unit

1   To be able to define logistics systems' components
2   To be able to identify solutions to real logistics problems
3   To be able to use Matlog software
4   To be able to model city logistics problems
5   To be able to solve city logistics problems

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to logistics system modeling
2 Facility location: Great-circle distances and geocoding; minimum cost network flow; continuous single- and multi-facility minisum location; location-allocation.
3 Introduction to Matlog software
4 Solving facility location problems using Matlab
5 Freight transport: Freight transportation systems; independent truck transport charge; LTL tariffs and rates; total logistics cost.
6 Modelling City Logistics
7 City Logistics with Intelligent Transport Systems
8 Case studies on City Logistics
9 Case studies on City Logistics
10 Location of Logistics Terminals
11 Vehicle Routing Problem
12 Solving VRP problems using Matlab
13 Solving VRP problems using Matlab
14 Solving VRP problems using Matlab

Recomended or Required Reading

Taniguchi, E., Thompson,R.G., Yamada, T., and van Duin, R. (2008) City Logistics: Network Modelling and Intelligent Transport Systems, Emerald Group Publishing.

Chopra, S., and Meindl, P. (2010). Supply Chain Management: Strategy, Planning, and Operations, 4th Ed., Prentice-Hall.

Planned Learning Activities and Teaching Methods

Course notes that are prepared using different sources (Books, journal papers, conference proceedings) will be given using board and visual presentations

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)

derya.eren@deu.edu.tr

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 6 84
Preparation for midterm exam 1 18 18
Preparation for final exam 1 20 20
Preparing assignments 1 30 30
Final 1 2 2
Midterm 1 2 2
Assignments/presentations 1 2 2
TOTAL WORKLOAD (hours) 200

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.14
LO.244
LO.34
LO.44
LO.54

CONTACT INFORMATION
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Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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