COURSE UNIT TITLE

: QUANTITATIVE DECISION MAKING

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IÜE 5030 QUANTITATIVE DECISION MAKING ELECTIVE 3 0 0 4

Offered By

Production Management and Industrial Business Administration

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSISTANT PROFESSOR MERT TOPOYAN

Offered to

Production Management and Industrial Business Administration

Course Objective

Explanation of quantitative methods used for decision-making in business, defining the decision problems and application of modeling and solution methods.

Learning Outcomes of the Course Unit

1   To define the decision-making problems.
2   To identify the components that affect decision-making problems.
3   To model decision-making problems.
4   To determine the appropriate method to be applied to decision-making problems.
5   To develop the most appropriate solution to decision-making problems.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 The general structure of the decision-making problems, defining the decision problem and model building.
2 Decision-making under uncertainty: Pessimism (maximin), optimism (Maximax), equal probability (Laplace), minimum override the loss of opportunity (Savage), Hurwicz criteria
3 Decision-making in case of risk: the expected value criterion, expected opportunity loss criterion, the expected value of full information, decision tree analysis
4 Decision-making in the case of competition: Game theory
5 Multi-criteria decision-making: AHP, ANP, TOPSIS
6 Multi-criteria decision-making: ELECTRA, MOORE, UTA
7 Multi-criteria decision-making: PROMETHEE, VIKOR, Gray Relationship Analysis
8 Linear Programming: Optimization
9 Linear Programming: Duality and exceptions
10 Nonlinear programming
11 Integer Programming
12 Dynamic Programming
13 Fuzzy Logic
14 The relationship of the results of quantitative decision making and managers judgements.

Recomended or Required Reading

Aydın Ulucan (2004), Yöneylem Araştırması: Işletmecilik Uygulamalı Bilgisayar Destekli Modelleme, Siyasal Kitabevi, Ankara
Erkut Düzakın (2005), Işletme Yöneticileri Için Excel ile Sayısal Karar Verme Teknikleri, Kare Yayınları, Istanbul
Cemal Özgüven (2003), Doğrusal Programlama ve Uzantıları, Detay Yayıncılık, Ankara
Aşkın Özdağoğlu (2011), Çok Ölçütlü Karar Verme Yöntemleri ve Uygulama Örnekleri, TMMOB Makine Mühendisleri Odası, Yayın No: MMO/570, Izmir

Planned Learning Activities and Teaching Methods

Interactive lectures, case studies, discussion

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 STT TERM WORK (SEMESTER)
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + STT * 0.30 + FIN* 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.30 + RST* 0.40


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 14 3 42
Preparations before/after weekly lectures 14 1 14
Preparation for midterm exam 1 10 10
Preparation for final exam 1 10 10
Preparing assignments 1 20 20
Preparing presentations 1 3 3
Midterm 1 2 2
Final 1 2 2
TOTAL WORKLOAD (hours) 103

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.111
LO.2111
LO.3111
LO.411
LO.511