Introducing the Genetic Algorithm and Direct Search Toolbox
What Is the Genetic Algorithm and Direct Search Toolbox?
Related Products
Writing an M-File for the Function You Want to Optimize
Example -- Writing an M-File
Maximizing Versus Minimizing
Getting Started with the Genetic Algorithm
What Is the Genetic Algorithm?
Using The Genetic Algorithm
Calling the Function ga at the Command Line
Using the Genetic Algorithm Tool
Example: Rastrigin's Function
Rastrigin's Function
Finding the Minimum of Rastrigin's Function
Finding the Minimum from the Command Line
Displaying Plots
Some Genetic Algorithm Terminology
Fitness Functions
Individuals
Populations and Generations
Diversity
Fitness Values and Best Fitness Values
Parents and Children
How the Genetic Algorithm Works
Outline of the Algorithm
Initial Population
Creating the Next Generation
Plots of Later Generations
Stopping Conditions for the Algorithm
Getting Started with Direct Search
What Is Direct Search?
Performing a Pattern Search
Calling patternsearch at the Command Line
Using the Pattern Search Tool
Example: Finding the Minimum of a Function
Objective Function
Finding the Minimum of the Function
Plotting the Objective Function Values and Mesh Sizes
Pattern Search Terminology
Patterns
Meshes
Polling
How Pattern Search Works
Iterations 1 and 2: Successful Polls
Iteration 4: An Unsuccessful Poll
Displaying the Results at Each Iteration
More Iterations
Stopping Conditions for the Pattern Search
Examples
Using the Genetic Algorithm
Overview of the Genetic Algorithm Tool
Opening the Genetic Algorithm Tool
Defining a Problem in the Genetic Algorithm Tool
Running the Genetic Algorithm
Pausing and Stopping the Algorithm
Displaying Plots
Example -- Creating a Custom Plot Function
Reproducing Your Results
Setting Options for the Genetic Algorithm
Importing and Exporting Options and Problems
Example -- Resuming the Genetic Algorithm from the Final Population:
Generating an M-File
Using the Genetic Algorithm at the Command Line
Running the Genetic Algorithm with the Default Options
Setting Options at the Command Line
Using Options and Problems from the Genetic Algorithm Tool
Reproducing Your Results
Resuming ga from the Final Population of a Previous Run
Running ga from an M-File
Setting Options for the Genetic Algorithm
Diversity
Population Options
Fitness Scaling Options
Selection Options
Reproduction Options
Mutation and Crossover
Mutation Options
The Crossover Fraction
Comparing Results for Varying Crossover Fractions
Example -- Global Versus Local Minima
Setting the Maximum Number of Generations
Using a Hybrid Function
Vectorize Option
Using Direct Search
Overview of the Pattern Search Tool
Opening the Pattern Search Tool
Defining a Problem in the Pattern Search Tool
Running a Pattern Search
Example -- A Constrained Problem
Pausing and Stopping the Algorithm
Displaying Plots
Setting Options
Importing and Exporting Options and Problems
Generate M-File
Performing a Pattern Search from the Command Line
Performing a Pattern Search with the Default Options
Setting Options
Using Options and Problems from the Pattern Search Tool
Setting Pattern Search Options
Poll Method
Complete Poll
Using a Search Method
Mesh Expansion and Contraction
Mesh Accelerator
Cache Options
Setting Tolerances for the Solver
Functions -- Listed by Category
Genetic Algorithm
Direct Search
Genetic Algorithm Options
Plot Options
Population Options
Fitness Scaling Options
Selection Options
Reproduction Options
Mutation Options
Crossover Options
Migration Options
Output Function Options
Stopping Criteria Options
Hybrid Function Option
Vectorize Option
The State Structure
Pattern Search Options
Plot Options
Poll Options
Search Options
Mesh Options
Cache Options
Stopping Criteria
Output Function Options
Display to Command Window Options
Vectorize Option
Alphabetical List of Functions
Printable Documentation (PDF)
Release Notes