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  Course Description
Course Name : Optimisation I

Course Code : TS-505

Course Type : Optional

Level of Course : Second Cycle

Year of Study : 1

Course Semester : Fall (16 Weeks)

ECTS : 6

Name of Lecturer(s) : Prof.Dr. MAHMUT ÇETİN

Learning Outcomes of the Course : 1. Learns system concept.
2. Helps sutudents increase their ability to formulate mathematically simple sentences.
3. Learns optimisation concept and problem solving.
4. Knows how to obtain infinite solutions; interprets solution sets, and preserves natural resources by practicing these techniques.

Mode of Delivery : Face-to-Face

Prerequisites and Co-Prerequisites : None

Recommended Optional Programme Components : None

Aim(s) of Course : The aims of the course are to formulate engineering problems by using systems approach, to interpret mathematical solutions, to chose optimal solution, and find practical solutions faced in real life.

Course Contents : Introduction; system concept; linear programming; geometric solution of linear programming, non-negative slack variables; Simplex algorithm of Dantzig, duality, sensitivity analysis; transportation problems

Language of Instruction : Turkish

Work Place : Class


  Course Outline /Schedule (Weekly) Planned Learning Activities
Week Subject Student's Preliminary Work Learning Activities and Teaching Methods
1 Introduction Books and other study materials Self-study plus lecturing
2 System concept Books and other study materials Self-study plus lecturing
3 Introduction to linear programming Books and other study materials Self-study plus lecturing
4 Linear programming Books and other study materials Self-study plus lecturing
5 Geometric solution of linear programming problems Books and other study materials Self-study plus lecturing
6 Geometric solution of linear programming problems (CONT.) Books and other study materials Self-study plus lecturing
7 Slack variables Books and other study materials Self-study plus lecturing
8 Slack variables (CONT.) Books and other study materials Self-study plus lecturing
9 Basic definitions and simplex based solution methods Books and other study materials Self-study plus lecturing
10 Mid-term exam Books and other study materials Take-home exam
11 Simplex based solution methods (CONT.) Books and other study materials Self-study plus lecturing
12 Practical problems Books and other study materials Self-study plus lecturing
13 Duality (optimization) Books and other study materials Self-study plus lecturing
14 Sensitivity analysis Books and other study materials Self-study plus lecturing
15 Transportation problems Books and other study materials Self-study plus lecturing
16/17 Final exam Books and other study materials Take-home exam


  Required Course Resources
Resource Type Resource Name
Recommended Course Material(s)  1. Tülücü, K. 1997.Linear programming. Ç.Ü.Z.F. Ders.K.No:18.
 2. Bernard Kolman, Robert E. Beck, 1995. Elementary Linear Programming with Applications. Academic Press, ISBN# 012417910X, 9780124179103.
Required Course Material(s)


  Assessment Methods and Assessment Criteria
Semester/Year Assessments Number Contribution Percentage
    Mid-term Exams (Written, Oral, etc.) 1 80
    Homeworks/Projects/Others 4 20
Total 100
Rate of Semester/Year Assessments to Success 40
 
Final Assessments 100
Rate of Final Assessments to Success 60
Total 100

  Contribution of the Course to Key Learning Outcomes
# Key Learning Outcome Contribution*
1 Has the ability to develop and deepen the level of expertise degree qualifications based on the knowledge acquired in the field of agriculture and irrigation structures 3
2 Has the ability to understand the interaction between irrigation and agricultural structures and related disciplines 2
3 Qualified in devising projects in agricultural structures and irrigation systems. 4
4 Conducts land applications,supervises them and assures of development 3
5 Has the ability to apply theoretical and practical knowledge in the field of agricultural structures and irrigation department 5
6 Has the ability to support his specilist knowledge with qualitative and quantitative data. Can work in different disciplines. 5
7 Solves problems by establishing cause and effect relationship 3
8 Able to carry out a study independently on a subject. 1
9 Has the ability to design and apply analytical, modelling and experimental researches, to analyze and interpret complex issues occuring in these processes. 4
10 Can access resources on his speciality, makes good use of them and updates his knowledge constantly. 0
11 Has the ability to use computer software in agricultural structures and irrigation; can use informatics and communications technology at an advanced level. 3
* Contribution levels are between 0 (not) and 5 (maximum).

  Student Workload - ECTS
Works Number Time (Hour) Total Workload (Hour)
Course Related Works
    Class Time (Exam weeks are excluded) 14 3 42
    Out of Class Study (Preliminary Work, Practice) 14 2 28
Assesment Related Works
    Homeworks, Projects, Others 4 12 48
    Mid-term Exams (Written, Oral, etc.) 1 10 10
    Final Exam 1 10 10
Total Workload: 138
Total Workload / 25 (h): 5.52
ECTS Credit: 6