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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS END 2418 INTRODUCTION TO MATHEMATICAL MODELING COMPULSORY 3 0 0 5

Offered By

Industrial Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR MUALLA GONCA AVCI

Offered to

Industrial Engineering

Course Objective

The aim of this course is to teach students linear algebra, linear equation systems, solution approaches for linear equation systems, manufacturing and service systems modeling by linear programming.

Learning Outcomes of the Course Unit

1   To be informed about basic concepts of linear algebra 2   To be informed about linear equation systems and solution approaches 3   To be informed about basic concepts of linear programming 4   To be able to develop a suitable mathematical model for an optimization problem

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to mathematical modeling 2 Introduction to linear algebra, linear equation systems, linear transformations 3 Matrix operations, transpose of a matrix, inverse of a matrix 4 Rank of a matrix, linear independence 5 Determinants, Cramer s rule 6 Vectors, vector spaces, eigenvalue and eigenvector 7 Solution of linear equation systems: Gauss-Jordan Method 8 Introduction to linear programming 9 Convex sets, extreme points and optimal solution in linear programming 10 Graphical solution of two-variable linear programming problems 11 Simplex algorithm, matrix representation of an optimal tableau of a linear programming model 12 Closed form representation of mathematical models 13 Examples to linear programming models 14 Examples to linear programming models

Recomended or Required Reading

David C. Lay, Linear Algebra and Its Applications. Wayne L. Winston, Operations Research: Applications and Algorithms.

Planned Learning Activities and Teaching Methods

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 PRC PRACTICE 3 FIN FINAL EXAM 4 FCG FINAL COURSE GRADE MTE*0.35+PRC *0.15+FIN * 0.50 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE*0.35+PRC *0.15+RST * 0.50

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 12 3 36 Tutorials 2 3 6 Preparations before/after weekly lectures 14 2 28 Preparation for midterm exam 1 26 26 Preparation for final exam 1 26 26 Final 1 2 2 Midterm 1 1 1 TOTAL WORKLOAD (hours) 125

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 LO.1 2 LO.2 2 LO.3 2 LO.4 2