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Programme Information

Faculty Of Engıneerıng
Electrıcal And Electronıcs Engıneerıng (Englısh) General Information Administration Programme Outcomes Academic Staff Curriculum 1st Year 2nd Year 3rd Year 4th Year Degree Programmes Toros University Information Package Bologna Process Action Plan Toros University

Faculty Of Engıneerıng
Electrıcal And Electronıcs Engıneerıng (Englısh)

Course Information

OPTIMIZATION METHODS
Code Semester Theoretical Practice National Credit ECTS Credit
Hour / Week
CSE433 Fall 3 0 3 5

Prerequisites and co-requisites
Language of instruction English
Type Elective
Level of Course Bachelor's
Lecturer Asst. Prof. Omid SHARIFI
Mode of Delivery Face to Face
Suggested Subject
Professional practise ( internship ) None
Objectives of the Course Mathematical Programming: Linear, Integer and Quadratic Programs - Linear Programming: Simplex and Dual Simplex Methods, Duality and Precision Analysis, Expansions - Integer Programming: Branch Boundary, Cutting and Transportation Algorithms - Nonlinear Programming: Single Variable Optimization, Multivariate Constrained and Unconstrained CPM - Inventory Models - Estimation Models: Regression Methods, Plane Methods - Game Theory - Decision Theory - Markov Processes - Queuing Systems: Optimization - Dynamic Programming - Network Analysis: Minimum Span, Shortest Path, and Maximum Flow Problems - Project Management: PERT / CPM - M / M / 1, M / M / s, M / M / 1 / K and M / M / s / K Systems
Contents of the Course Mathematical Programming: Linear, Integer and Quadratic Programs - Linear Programming: Simplex and Dual Simplex Methods, Duality and Precision Analysis, Expansions - Integer Programming: Branch Boundary, Cutting and Transportation Algorithms - Nonlinear Programming: Single Variable Optimization, Multivariate Constrained and Unconstrained CPM - Inventory Models - Estimation Models: Regression Methods, Plane Methods - Game Theory - Decision Theory - Markov Processes - Queuing Systems: Optimization - Dynamic Programming - Network Analysis: Minimum Span, Shortest Path, and Maximum Flow Problems - Project Management: PERT / CPM - M / M / 1, M / M / s, M / M / 1 / K and M / M / s / K Systems

Learning Outcomes of Course

# Learning Outcomes
1 Provides solutions to engineering problems
2 The lecture informs the student about optimization science.
3 The lecture solves the problems that are related to optimization.
4 The latest technological developments are taught in optimization science.

Course Syllabus

# Subjects Teaching Methods and Technics
1 Mathematical Programming: Linear, Integer and Quadratic Programs Lecture
2 Mathematical Programming: Linear, Integer and Quadratic Programs Lecture
3 Linear Programming: Simplex and Dual Simplex Methods, Duality and Precision Analysis, Expansions Lecture
4 Integer Programming: Branch Bounding, Cutting and Transportation Algorithms Lecture
5 Nonlinear Programming: Single Variable Optimization, Multivariate Constrained and Unconstrained Optimization Lecture
6 Dynamic Programming Lecture
7
8 Network Analysis: Minimum Propagation, Shortest Path, and Maximum Flow Problems Lecture
9 Project Management: PERT / CPM - Inventory Models Lecture
10 Estimation Modeler: Regression Methods, Leveling Methods Lecture
11 Game Theory Lecture
12 Decision Theory Lecture
13 Markov Processes - Queuing Systems: M / M / 1, M / M / s, M / M / Lecture
14
15
16 Final Exam

Course Syllabus

# Material / Resources Information About Resources Reference / Recommended Resources
1 Optimization methods books, internet resources

Method of Assessment

# Weight Work Type Work Title
1 40% Mid-Term Exam Mid-Term Exam
2 60% Final Exam Final Exam

Relationship between Learning Outcomes of Course and Program Outcomes

# Learning Outcomes Program Outcomes Method of Assessment
1 Provides solutions to engineering problems 1 1͵2
2 The lecture informs the student about optimization science. 1 1͵2
3 The lecture solves the problems that are related to optimization. 1 1͵2
4 The latest technological developments are taught in optimization science. 1 1͵2
PS. The numbers, which are shown in the column Method of Assessment, presents the methods shown in the previous table, titled as Method of Assessment.

Work Load Details

# Type of Work Quantity Time (Hour) Work Load
1 Course Duration 14 3 42
2 Course Duration Except Class (Preliminary Study, Enhancement) 0 0 0
3 Presentation and Seminar Preparation 0 0 0
4 Web Research, Library and Archival Work 0 0 0
5 Document/Information Listing 0 0 0
6 Workshop 0 0 0
7 Preparation for Midterm Exam 1 10 10
8 Midterm Exam 1 1 1
9 Quiz 0 0 0
10 Homework 0 0 0
11 Midterm Project 0 0 0
12 Midterm Exercise 0 0 0
13 Final Project 0 0 0
14 Final Exercise 0 0 0
15 Preparation for Final Exam 0 0 0
16 Final Exam 1 72 72
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