inspyred: Bio-inspired Algorithms in Python

• Overview
  • Bio-inspired Computation
  • Design Methodology
  • Installation
  • Getting Help
• Tutorial
  • The Rastrigin Function
    • The Generator
    • The Evaluator
    • The Evolutionary Computation
  • Evolving Polygons
    • The Generator
    • The Evaluator
    • The Bounder
    • The Observer
    • The Evolutionary Computation
  • Lunar Explorer
    • The Generator
    • The Evaluator
    • The Evolutionary Computation
• Examples
  • Standard Algorithms
    • Genetic Algorithm
    • Evolution Strategy
    • Simulated Annealing
    • Differential Evolution Algorithm
    • Estimation of Distribution Algorithm
    • Pareto Archived Evolution Strategy (PAES)
    • Nondominated Sorting Genetic Algorithm (NSGA-II)
    • Particle Swarm Optimization
    • Ant Colony Optimization
  • Customized Algorithms
    • Custom Evolutionary Computation
    • Custom Archiver
    • Custom Observer
    • Custom Replacer
    • Custom Selector
    • Custom Terminator
    • Custom Variator
  • Advanced Usage
    • Discrete Optimization
      • The Traveling Salesman Problem
      • The Knapsack Problem
    • Evaluating Individuals Concurrently
      • The multiprocessing Module
      • Parallel Python
    • Island Models
    • Replacement via Niching
• Recipes
  • Lexicographic Ordering
  • Constraint Selection
  • Meta-Evolutionary Computation
  • Micro-Evolutionary Computation
  • Network Migrator
• Library Reference
  • Evolutionary Computation
    • ec – Evolutionary computation framework
    • emo – Evolutionary multiobjective optimization
    • analysis – Optimization result analysis
    • utilities – Optimization utility functions
    • Operators
      • archivers – Solution archival methods
      • evaluators – Fitness evaluation methods
      • generators – Solution generation methods
      • migrators – Solution migration methods
      • observers – Algorithm monitoring methods
      • replacers – Survivor replacement methods
      • selectors – Parent selection methods
      • terminators – Algorithm termination methods
      • variators – Solution variation methods
  • Swarm Intelligence
    • swarm – Swarm intelligence
    • topologies – Swarm topologies
  • Benchmark Problems
    • benchmarks – Benchmark optimization functions
    • Single-Objective Benchmarks
    • Multi-Objective Benchmarks
    • Discrete Optimization Benchmarks
• Troubleshooting
  • Always Store the Seed
  • Use and Consult the Logs
  • Choose Operators that Work Together

Indices

• Index
• Module Index
• Search Page