PYCELLGA Documentation

Table of Contents :

  • Installation
    • Requirements
    • Installing from PyPI
    • Installing from Source
    • Optional Dependencies
    • Verifying the Installation
    • Troubleshooting
    • Uninstallation
  • pycellga: A Comprehensive Guide
    • Neighborhood Operators
      • Linear 5
        • Linear5
      • Linear 9
        • Linear9
      • Compact 9
        • Compact9
      • Compact 13
        • Compact13
      • Compact 21
        • Compact21
      • Compact 25
        • Compact25
    • Mutation Operators
      • Bit Flip Mutation
        • BitFlipMutation
      • Byte-Level Mutation
        • ByteMutation
      • Randomized Byte Mutation
        • ByteMutationRandom
      • Uniform Float Mutation
        • FloatUniformMutation
      • Insertion-Based Mutation
        • InsertionMutation
      • Shuffle Mutation
        • ShuffleMutation
      • Swap Mutation
        • SwapMutation
      • Two-Opt Mutation
        • TwoOptMutation
    • Recombination Operators
      • Arithmetic Crossover
        • ArithmeticCrossover
      • BLX-Alpha Crossover
        • BlxalphaCrossover
      • Byte One-Point Crossover
        • ByteOnePointCrossover
      • Byte Uniform Crossover
        • ByteUniformCrossover
      • Flat Crossover
        • FlatCrossover
      • Linear Crossover
        • LinearCrossover
      • One-Point Crossover
        • OnePointCrossover
      • Partially Matched Crossover (PMX)
        • PMXCrossover
      • Two-Point Crossover
        • TwoPointCrossover
      • Unfair Average Crossover
        • UnfairAvarageCrossover
      • Uniform Crossover
        • UniformCrossover
    • Selection Operators
      • Tournament Selection
        • TournamentSelection
      • Roulette Wheel Selection
        • RouletteWheelSelection
    • Problem Definitions
      • Abstract Problem Base
        • AbstractProblem
      • Single-Objective Problems
        • Single-Objective Optimization Problems
    • Example Implementations in pycellga
      • Available Example Modules
        • ExampleProblem
        • run_alpha_cga_example()
        • ExampleProblem
        • run_ccga_example()
        • ExampleProblem
        • run_cga_example()
        • RealProblem
        • run_mcccga_example()
        • ExampleProblem
        • run_sync_cga_example()
    • Core Modules
    • Population Management
      • OptimizationMethod
        • OptimizationMethod.ALPHA_CGA
        • OptimizationMethod.CCGA
        • OptimizationMethod.CGA
        • OptimizationMethod.MCCCGA
        • OptimizationMethod.SYNCGA
      • Population
        • Population.method_name
        • Population.ch_size
        • Population.n_rows
        • Population.n_cols
        • Population.gen_type
        • Population.problem
        • Population.vector
        • Population.__init__()
        • Population.initial_population()
    • Individual Representation
      • GeneType
        • GeneType.BINARY
        • GeneType.PERMUTATION
        • GeneType.REAL
      • Individual
        • Individual.chromosome
        • Individual.fitness_value
        • Individual.position
        • Individual.neighbors_positions
        • Individual.neighbors
        • Individual.gen_type
        • Individual.ch_size
        • Individual.__init__()
        • Individual.generate_candidate()
        • Individual.getneighbors()
        • Individual.getneighbors_positions()
        • Individual.randomize()
        • Individual.setneighbors()
        • Individual.setneighbors_positions()
    • Grid Structure
      • Grid
        • Grid.n_rows
        • Grid.n_cols
        • Grid.__init__()
        • Grid.make_2d_grid()
    • Byte Operators
      • bits_to_float()
      • bits_to_floats()
      • float_to_bits()
      • floats_to_bits()
    • Optimizer
      • Result
        • Result.__init__()
        • Result.chromosome
        • Result.fitness_value
        • Result.generation_found
      • alpha_cga()
      • ccga()
      • cga()
      • compete()
      • generate_probability_vector()
      • mcccga()
      • random_vector_between()
      • sample()
      • sync_cga()
      • update_vector()
  • Usage Examples
    • cga (Cellular Genetic Algorithm)
    • Example Problem
    • ExampleProblem Class
    • Usage
  • Contributing
    • Ways to Contribute
    • Development Setup
    • Pull Request Guidelines
    • Coding Standards
    • Running Tests
  • Citing
PYCELLGA Documentation
  • Search

© Copyright 2024, Sevgi Akten Karakaya, Mehmet Hakan Satman.

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