COURSE UNIT TITLE

: QUANTITATIVE TECHNIQUES IN INDUSTRIAL ENGINEERING

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
END 3977 QUANTITATIVE TECHNIQUES IN INDUSTRIAL ENGINEERING ELECTIVE 3 0 0 5

Offered By

Industrial Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR KEMAL SUBULAN

Offered to

Industrial Engineering

Course Objective

In the scope of this course, linear programming, integer programming, nonlinear programming, stochastic programming, fuzzy mathematical programming, multi-objective optimization, constraint programming models will be developed for solving some fundamental problems in Industrial Engineering area and also solved by making use of various optimization software. The aim of this course is to provide more detailed information about advanced operations research techniques and to gain the ability of applying required techniques (linear programming, integer programming, nonlinear programming, stochastic programming, fuzzy mathematical programming, multi-objective optimization, constraint programming, etc.) for solving some fundamental Industrial Engineering problems under deterministic and uncertain environments.

Learning Outcomes of the Course Unit

1   To have knowledge of various quantitative techniques utilized for achieving the solution of Industrial Engineering problems.
2   To gain the ability of developing integer linear programming models for Industrial Engineering problems and solving them by using an optimization software.
3   To gain the ability of solving nonlinear programming models with an optimization software.
4   To gain the ability of developing stochastic programming models for some optimization problems with random uncertainties and solving them by using an optimization software.
5   To gain the ability of developing fuzzy mathematical programming models for some optimization problems with fuzzy uncertainties and transforming them into deterministic equivalent forms with some transformation methods and solving them with an optimization software.
6   To gain the ability of solving multi-objective optimization problems with an optimization software.
7   To gain the ability of developing constraint programming models of Industrial Engineering problems and solving them with an optimization software.
8   To gain the ability of developing a multi-objective fuzzy-stochastic programming model for a given Industrial Engineering problem in accordance with the instructions in the term project directive, and the ability of effectively writing and presenting the project report including the solution of this problem that is provided by an optimization software.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

END 3525 - OPERATIONS RESEARCH I

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction of basic quantitative techniques in Industrial Engineering
2 Integer linear programming applications with LINGO and IBM ILOG CPLEX Optimization Studio
3 Integer linear programming applications with GAMS and Python Gurobi solver
4 Convex and concave functions and nonlinear programming applications with LINGO
5 Nonlinear programming applications with LINGO and GAMS
6 Single and multi-stage stochastic programming applications with LINGO and GAMS
7 Chance constrained stochastic programming applications with LINGO and GAMS
8 Fuzzy mathematical programming and the fundamentals of transformation methods
9 Fuzzy mathematical programming applications with LINGO and IBM ILOG CPLEX Optimization Studio
10 Multi-objective optimization techniques: Fuzzy goal programming, compromise programming, Epsilon constraint method
11 Multi-objective optimization applications with Python Gurobi solver
12 Constraint programming applications with IBM ILOG CPLEX Optimization Studio
13 Constraint programming applications with IBM ILOG CPLEX Optimization Studio
14 Mat-heuristic algorithm implementations via Python Gurobi solver

Recomended or Required Reading

1. Operations Research: Applications and Algorithms, Cengage Learning, Wayne L. Winston (2003).
2. Quantitative Analysis for Management, Pearson, Prentice Hall, Render B., Stair, R.M., Hanna, M.E.An Introduction to Management Science Quantitative Approaches to Decision Making, South-Western Cengage Learning (2009).
3. Stochastic Programming: Modeling Decision Problems Under Uncertainty. Willem K. Klein Haneveld , Maarten H. van der Vlerk , Ward Romeijnders, Springer Cham, (2020).
4. Fuzzy Stochastic Optimization: Theory, Models and Applications. Shuming Wang, Junzo Watada, Springer New York, NY (2012).

Planned Learning Activities and Teaching Methods

Case studies and applications by using optimization software ve presentations.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 PRJ PROJECT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.20 + PRJ * 0.40 + FIN * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.20 + PRJ * 0.40 + RST * 0.40


Further Notes About Assessment Methods

None

Assessment Criteria

Midterm exam (%20) + Project (%40) + Final Exam (%40)

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Assoc. Prof. Dr. Kemal Subulan
e-mail adress: kemal.subulan@deu.edu.tr
Phone: +90 232 301 76 24

Office Hours

Fridays afternoons from 15:00 to 17:00.

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 3 3
Preparation for final exam 1 4 4
Preparing assignments 4 4 16
Preparing presentations 14 2 28
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 125

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.122
LO.235432
LO.335432
LO.435432
LO.535432
LO.635432
LO.735432
LO.8332

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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