GenesPHP

A pure PHP genetic algorithms library. The intention is to create a library without any strange dependency. Pure PHP.

Usage guide for a simple case

1. Create a Task object.

   $task = new \genesphp\Task();
   

2. Write your own evaluation function. This function must accept two parameters:

   • An array (the genome). Each item in the list is a gene.
   • An arbitrary object (which is defined by you, as complementary data to evaluate the individuals). By default, this object is Null.

   The function must return a floating value as fitness of the individual.

   function my_eval_function(&$genome, &$data) {  // Reference is recomended
       // x - $genome[0]
       // y - $genome[1]
   
       return ($genome[0] * $data[0]) + ($genome[1] * $data[1]);
   }
   

3. Define the structure of your variables. These can be floating values, binary strings, or permutations:

   // Declaration of binary string structure as array of arrays (2 variables)
   $struct = [[true, 5, 5],   // x (sign bit, integer bits, mantissa bits)
              [true, 5, 5]];   // y (sign bit, integer bits, mantissa bits)
   

4. Create a population and assign to the Task object.

   $the_pop = \genesphp\init_binary_pop($n, $struct);
   $data = [5, 20];  // Arbitrary data
   $task->set_population($the_pop);
   $task->set_data($data);
   

5. Choose the selection, crossover and mutation functions that will be used, and assign them to the Task object as well.

   $task->set_evals(
       ['example_evaluation_function'],
       [-1.0]);  // (-1 minimizes, +1 maximizes)
   $task->set_mutator('\\genesphp\\mutate_flip', ['mp' => .3]);
   $task->set_crossover('\\genesphp\\crossover_one_point');
   $task->set_selector('\\genesphp\\select_vasconcelos', ['cp' => .5]);
   

6. Define the desired execution parameters (generations, execution times, etc.). Choose a genetic algorithm and ...

7. Run it!

   $elitism = 1.0;  // % of puplation in elitism
   $duration = 10;  // Max duration (in seconds)
   $gens = 1000;  // Maximum number of generations
   $verbose = 2;  // Report every n generations
   $answer = \genesphp\general_ga(
       $task,
       $elitism,
       $duration,
       $gens,
       $verbose
   )
   

More examples

Check the examples directory to see the solution of simple problems, using different ways to encode the genome.

TODO

• Documentation
• More selection algorithms
• Add multiobjective selector(s)
• More mutation operators
• More crossover operators
• User documentation and examples