ARTIFICIAL INTELLIGENCE ENGINEERING
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
LOG4436	Inventory and Warehouse Management	Spring	3	0	3	6

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Prof. Dr. YAVUZ GÜNALAY
Recommended Optional Program Components:	None
Course Objectives:	Students learn to analytically solve problems and make decision considering forecasting, inventory planning and service levels, profitability, product range, supply chain dynamics, facility location, distribution, and routing.

Learning Outcomes

The students who have succeeded in this course;
The course provides an integrated methodology for strategy based inventory and product management in supply chains.

Course Content

Course introduction, Measures in logistics, ABCD analysis, Activity based costing, Du Pont -model, Turnover, Modeling in logistics, Trend adjustment: Holt’s method, Trend and seasonal variation adjustment: Winter’s model, optimizing the parameters for the above methods, Stochastic demand, Safety stocks, Single products with time-variable demand, dynamic programming, Wagner-Whitin method, Silver-Meal heuristics, Time supply, Lot- forlot, Least unit cost, Part-period balancing, Heuristics, Yield Management – stochastic demand, Bullwhip effect, Deterministic demand, Probabilistic demand, Arborescent system, Supply chain contracts, Distribution requirements planning, Multioperiod production planning, Repair crew planning.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Course introduction, Measures in logistics, ABCD analysis
2)	Activity based costing
3)	Du-Pont Model, Turnover, Modeling in Logistics
4)	Trend adjustment: Holt’s method, Trend and seasonal variation adjustment: Winter’s model, optimizing the parameters for the above methods
5)	Stochastic demand, Safety stocks, Single products with time-variable demand, dynamic programming
6)	Wagner-Whitin method, Silver-Meal heuristics, Time supply, Lot- forlot, Least unit cost, Part-period balancing, Heuristics
7)	Yield Management – stochastic demand
8)	Midterms Week
9)	Bullwhip effect, Deterministic demand, Probabilistic demand, Arborescent system, Supply chain contracts, Distribution requirements planning
10)	Multioperiod production planning, Repair crew planning
11)	Case Capacent - preparation
12)	Case Capacent feedback session
13)	Course Wrapup; Case Sport Obermeyer feedback session
14)	Finals Week

Sources

Course Notes / Textbooks:	Silver, Edward A. (1998) Inventory management and production planning and scheduling. ISBN 0-471-11947-4.
References:	Ders Notları - Lecture material and course reading package.

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Homework Assignments	5	% 30
Midterms	1	% 30
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 40
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Study Hours Out of Class	14	3	42
Homework Assignments	5	12	60
Midterms	1	2	2
Final	1	2	2
Total Workload			148

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Have sufficient background in mathematics, science and artificial intelligence engineering.
2)	Use theoretical and applied knowledge in the fields of mathematics, science and artificial intelligence engineering together for engineering solutions.
3)	Identify, define, formulate and solve engineering problems, select and apply appropriate analytical methods and modeling techniques for this purpose.
4)	Analyse a system, system component or process and design it under realistic constraints to meet desired requirements; apply modern design methods in this direction.
5)	Select and use modern techniques and tools necessary for engineering applications.
6)	Design and conduct experiments, collect data, and analyse and interpret results.
7)	Work effectively both as an individual and as a multi-disciplinary team member.
8)	Access information via conducting literature research, using databases and other resources
9)	Follow the developments in science and technology and constantly update themself with an awareness of the necessity of lifelong learning.
10)	Use information and communication technologies together with computer software with at least the European Computer License Advanced Level required by their field.
11)	Communicate effectively, both verbal and written; know a foreign language at least at the European Language Portfolio B1 General Level.
12)	Have an awareness of the universal and social impacts of engineering solutions and applications; know about entrepreneurship and innovation; and have an awareness of the problems of the age.
13)	Have a sense of professional and ethical responsibility.
14)	Have an awareness of project management, workplace practices, employee health, environment and work safety; know the legal consequences of engineering practices.