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• Basic information
• Learning outcomes
• Contents
• Assessment
• Workload

Basic information
Course title:	Computer Aided Quantitative Decision Making Techniques
Course code:	BUS 657
Lecturer:	Prof. Dr. Hakan KİTAPÇI
ECTS credits:	7.5
GTU credits:	3 (3+0+0)
Year, Semester:	1/2, Fall and Spring
Level of course:	Second Cycle (Master's)
Type of course:	Area Elective
Language of instruction:	Turkish
Mode of delivery:	Face to face
Pre- and co-requisites:	none
Professional practice:	No
Purpose of the course:	To have the students informed and gained skills about how to apply advanced quantitative techniques in computer to their business problems to be able to give right and speedy decisions.

Learning outcomes

Upon successful completion of this course, students will be able to:

1. This course offers managers how to use quantative decision making techniques in order to take rational decision making, and optimize production and services activities effectively

   Contribution to Program Outcomes

   1. Define and manipulate advanced concepts and common terminology of social sciences
   2. Critically review and contribute to the literature related to his/her area of expertise
   3. Formulate and solve advanced management problems concerning the issues of competitive strategy, investment and project management.
   4. Collect theoretical information about contemporary management issues and evaluate real cases in the light of them
   5. Identify the relationship between marketing management and consumer behaviors.
   6. Gain detailed information about strategic, tactical and operational dimensions of business management, analyze and design the business/company in organizational level
   7. Work effectively in multi-disciplinary research teams
   8. Develop an awareness of continuous learning in relation with modern technology
   9. Effectively express his/her research ideas and findings both orally and in writing
   10. Defend research outcomes at seminars and conferences.

   Method of assessment

   1. Written exam
   2. Oral exam
   3. Homework assignment
   4. Seminar/presentation

Contents
Week 1:	Linear programming, Integer programming.
Week 2:	Linear goal programming, Integer goal programming.
Week 3:	Quadratic programming, Integer quadratic programming.
Week 4:	Network models.
Week 5:	Nonlinear programming. Project.
Week 6:	Dynamic programming.
Week 7:	Project programming and aplication. Midterm exam
Week 8:	Queing analysis, queing system simulation.
Week 9:	Inventory theory and systems.
Week 10:	Forecasting models, Decision analysis.
Week 11:	Markov process.
Week 12:	Quality control charts.
Week 13:	Job scheduling.
Week 14:	Facility location and layout, Material requirement planning.
Week 15*:	...
Week 16*:	Presentation of Projects. Final exam
Textbooks and materials:
Recommended readings:	KAZAN, Halim., Bilgisayar Destekli Kantitatif Karar Verme Teknikleri (Yayınlanmamış Ders Notları), Kantitatif Karar Verme Teknikleri Yöneylem Araştırması Osman Halaç ALFA / İşletme-İktisat-Muhasebe Dizisi Behçet Altaylı: Simülasyon Kullanımı ile Sistem İyileştirme. Hava Kuvvetleri Komutanlığı 1994 Applied Operations Research: Examples from Defense Assessment by R. W. Shephard, Plenum, 1988. Yönetim Kararlarında Kantitatif Yöntemler - Yöneylem Araştırması Dr. Behçet Altaylı; Isbn: 975-96141-0-3; 605 Sayfa, Ciltli, Lüx Baskı)
	* Between 15th and 16th weeks is there a free week for students to prepare for final exam.

Assessment
Method of assessment	Week number	Weight (%)
Mid-terms:	7	20
Other in-term studies:		0
Project:	5	20
Homework:	10	20
Quiz:		0
Final exam:	16	40
	Total weight:	(%)

Workload
Activity	Duration (Hours per week)	Total number of weeks	Total hours in term
Courses (Face-to-face teaching):	3	14
Own studies outside class:	3	14
Practice, Recitation:	0	0
Homework:	6	10
Term project:	10	2
Term project presentation:	1	1
Quiz:	0	0
Own study for mid-term exam:	10	1
Mid-term:	1	1
Personal studies for final exam:	10	1
Final exam:	2	1
		Total workload:
		Total ECTS credits:	*
	* ECTS credit is calculated by dividing total workload by 25. (1 ECTS = 25 work hours)