Christini Lab Genetic Algorithm

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Introduction

Christini Lab version of the genetic algorithm originally published by Kumara Sastry at the Illinois Genetic Algorithms Laboratory (IlliGAL).

Reference:

Single & Multi-Objective Real-Coded Genetic Algorithms Code
Author: Kumara Sastry
Illinois Genetic Algorithms Laboratory (IlliGAL)
Deparment of General Engineering
University of Illinois at Urbana-Champaign
104 S. Mathews Ave, Urbana, IL 61801

This repository is intended to be used as a subtree of a fitting project. Follow the directions below to add/update the genetic algorithm to your repository.

Subtree installation:

Enter your local Git project

cd <PROJECT DIRECTORY>

Add remote URL of GA to your local project.

• -f - fetch from remote immediately
• GA_remote - Name of remote, you can change this

git remote add -f GA_remote https://github.com/Christini-Lab/Genetic_Algorithm.git

Add genetic algorithm as a subtree of the project.

• --prefix Genetic_Algorithm/ - prefix denotes the directory you wish to put the GA in, you can change this
• GA_remote - Model remote repository set earlier
• --squash - merges all commits into one for cleaner history

git subtree add --prefix Genetic_Algorithm/ GA_remote --squash

Updating the Genetic_Algorithm subtree:

Fetch any new changes, then pull changes into subtree directory.

• --prefix Genetic_Algorithm/ - Specify the model directory
• GA_remote - Model repository you will pull changes from
• master - Pulling in master branch changes, you can specify another branch if required

git subtree pull --prefix Genetic_Algorithm/ GA_remote master --squash

Loading initial populations:

A population file should be formated as follows:

• Number of solutions/individuals to be loaded
• Parameter values (one set of variables for each individual)
• Objective values (for each individual)
• Constraint values (for each individual)
• Penalty values (for each individual)

Example file below contains:

• 2 individuals
• 10 parameter values set to 1.0
• objective values set to 5

2

1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 5

1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 5

Christini Lab modifications:

• Separated directory structure, which includes examples and documentation
• Bulk of functions separated out of main function for easier readability and development
• Uses openMP to parallelize evaluations of each individual

Examples:

• sga_nsga - Original example from IllGAL. Contains 4 different setting files.

Documentation:

• Illigal - Original report/instructions from IlliGAL.

Development Notes:

Branching:

• Create new development branch for any unfinished features
• Features deemed to be necessity will be merged into master branch
• Optional features will be kept as separate feature branches

Code style:

• Follow 80 column rule
• No dangling whitespace
• New code generally follows Google C++ style