# Optimization Using Pattern Search Method MATLAB Programming

A Quick Way to Learn and Solve Optimization Problems in MATLAB. A Course for Beginners.

4/5

## Optimization Using Pattern Search Method MATLAB Programming

### What you’ll learn

Running direct search optimization problems in MATLAB
Specifying objective functions
Specifying constraints
Vectorizing objective function and constraints
Obtaining local and global optima
Parallel computing

### Requirements

MATLAB installed in your laptop/desktop computer

### Description

This course introduces applied direct search optimization in the MATLAB environment, focusing on using Global Optimization Toolbox. Various kinds of optimization problems are solved in this course. At the end of this course, you will be able to solve the optimization problems using the MATLAB. The complete MATLAB programs included in the class are also available for download.  Happy learning.NB: This course is designed most straightforwardly to utilize your time wisely.

### Overview

Section 1: Introduction to Optimization

Lecture 1 Welcome to the course

Lecture 2 Local optima and Global optima

Lecture 3 Single local solution, Multiple local solutions and Single global solution

Section 2: Objective or Fitness Functions

Lecture 4 What is Objective Function ?

Lecture 5 MATLAB Script For Single Objective Function

Lecture 6 MATLAB Script For Vectorized Function Call

Lecture 7 Passing Extra Parameters, Fixed Variables, or Data in the Objective Functions

Section 3: Direct/Pattern Search with MATLAB

Lecture 8 How Pattern Search Works?

Lecture 9 What is Direct/Pattern Search ?

Lecture 10 Unconstrained Pattern Search Minimization

Lecture 11 Pattern Search with a Linear Inequality Constraint

Lecture 12 Pattern Search with a Linear Equality Constraint

Lecture 13 Pattern Search with Bounds

Lecture 14 Pattern Search with Nonlinear Constraints

Lecture 15 Obtain Function Value And Minimizing Point

Lecture 16 Using a Complete Poll in a Generalized Pattern Search

Lecture 17 Vectorize the Objective and Constraint Functions

Lecture 18 Compute in Parallel

Lecture 19 Maximizing an Objective Function

Lecture 20 Stopping Criteria

Lecture 21 Exit Flag and Output

Anyone who is interested to solve optimization problems.,Researchers who want to publish ISI papers in this field.,Students who are working on optimization problems.

#### Course Information:

Udemy | English | 0h 49m | 234.02 MB
Created by: Karthik K

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