Implement aiNet for Optimization

[Joao-Paulo-Silva]

Objective

This issue aims to add a new algorithm to AISP: Opt-AiNet, a variation of the Ainet algorithm for optimization.

Details

The Opt-AiNet algorithm will be implemented in the INA(Immune Network Algorithm) module, applyying the principles of artificial immune network theory.

Project Structure

aisp/
  └─ ina/
      ├─ tests/
      ├─ __init__.py
      ├─ _ai_network.py
      └─ _opt_ai_network.py 

Important

• Reuse the existing mutation functions already implemented in project.
• Ensure that all four mutation methods are reviewed and validated for compatibility with the Ainet context:
  • clone_and_mutate_continuous
  • clone_and_mutate_binary
  • clone_and_mutate_ranged
  • clone_and_mutate_permutation

References

Below are some key references to support the implementation of technique:

• BROWNLEE, Jason. Immune Network Algorithm. Clever Algorithms, 2011. Available at: https://cleveralgorithms.com/nature-inspired/immune/immune_network_algorithm.html