Description

This course introduces the principles of Optimization Techniques. It provides the concepts of various classical and modern methods for constrained and unconstrained problems in both single and multivariable domains. The mathematical modeling and the transformation of optimization problems are also discussed. Many methods of modern optimization techniques are explored. The students will investigate and implement solutions of some real problems as case studies.

Program

Ph.D. in Computer Engineering

Objectives

The aim of the course is to give students the basic knowledge and tools to recognize, classify and solve different questions related to optimization problems and basic theory and methods for the solution of optimization problems.
The general objectives of the course are:
1. to introduce the fundamental concepts of Optimization Techniques
2. to make the learners aware of the importance of optimizations in real scenarios
3. to provide the concepts of various classical and modern methods of for constrained and unconstrained problems in both single and multivariable.

Textbook

Data will be available soon!

Course Content

content serial	Description
1	Optimality Principle, Performance Measures
2	Classification of Optimization Problems
3	Mathematical Modeling of Optimization problems
4	Transformation of Optimization Problems
5	Single and Multi variable optimization
6	Unconstrained Optimization
7	Constrained Optimization
8	Discrete Optimization
9	Robust Optimization
10	Dynamic Optimization
11	Stochastic Optimization methods
12	Nature inspired Optimization methods
13	Optimization Case Study-1 (Network Design)
14	Optimization Case Study-2 (Image - Video processing)
15	Optimization Case Study-3 (Big-data Analytics)

Markets and Career

Generation, transmission, distribution and utilization of electrical power for public and private sectors to secure both continuous and emergency demands.
Electrical power feeding for civil and military marine and aviation utilities.
Electrical works in construction engineering.

Degree Doctorate
Code: CC 805
Credit hrs: 3
Prequisites: None

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Advanced Optimization Techniques