BioInspired Computing Assignment

Introduction

Bioinspired computing assignment based on theoretical analysis among 10 bio-inspired computing algorithms and using PSO (Particle Swarm Optimization) to develop Self-Assembly PSO (SAPSO). We perform comparative studies with CSA (Classical Self-Assembly) Algorithm

Several Swarm Algorithm considered in this study were:

1. Particle Swarm Optimization
2. Grey Wolf Optimization
3. Ant Colony Optimization
4. Artificial Bee Colony Optimization
5. Bat Algorithm
6. Cuckoo Search Algorithm
7. Differential Evolution
8. FireFly Algorithm
9. Genetic Algorithm
10. Bee Colony Optimization

For the purpose of this study, we concluded that Particle Swarm Optimization would be the best fit to study and enhance the Classical Self-Assembly Algorithm for better performance and convergence.

File Descriptions

File	Purpose
Ant Colony Optimization.ipynb	Jupyter notebook of Ant Colony Optimization in Python
Artificial Bee Colony Optimization.ipynb	Jupyter notebook of Artiticial Bee Colony Optimization in Python
Bat Algorithm.ipynb	Jupyter notebook of Bat Algorithm in Python
Bee Colony Optimization.ipynb	Jupyter notebook of Bee Colony Optimization in Python
Classical Self-Assembly (CSA) and Self-Assembly Particle Swarm Optimizer (SAPSO).ipynb	Jupyter notebook of CSA and SAPSPO in Python
Cuckoo Search Algorithm.ipynb	Jupyter notebook of Cuckoo Search Algorithm in Python
Differential Evolution.ipynb	Jupyter notebook of Differential Evolution in Python
FireFly Algorithm.ipynb	Jupyter notebook of FireFly Algorithm in Python
Genetic Algorithm.ipynb	Jupyter notebook of Genetic Algorithm in Python
GreyWolfOptimization.ipynb	Jupyter notebook of Grey Wolf Optimization in Python
Particle Swarm Optimization.ipynb	Jupyter notebook of Particle Swarm Optimization in Python