Swarm Intelligence API
API reference for swarm intelligence algorithms in opt.swarm_intelligence.
Module Overview
python
from opt.swarm_intelligence import (
ParticleSwarm,
AntColony,
ArtificialBeeColony,
FireflyAlgorithm,
BatAlgorithm,
GreyWolf,
WhaleOptimization,
# ... and 50+ more algorithms
)Common Interface
All swarm intelligence algorithms inherit from AbstractOptimizer and implement:
python
class SwarmAlgorithm(AbstractOptimizer):
def __init__(
self,
func: Callable,
lower_bound: float,
upper_bound: float,
dim: int,
max_iter: int,
population_size: Optional[int] = None,
**kwargs
):
"""
Args:
func: Objective function to minimize
lower_bound: Lower bound for all dimensions
upper_bound: Upper bound for all dimensions
dim: Problem dimensionality
max_iter: Maximum iterations
population_size: Number of agents (algorithm-specific default if None)
"""
pass
def search(self) -> tuple[np.ndarray, float]:
"""
Execute optimization.
Returns:
Tuple of (best_solution, best_fitness)
"""
passAvailable Algorithms
See the Swarm Intelligence algorithms section for detailed documentation of each algorithm.
Example Usage
python
from opt.swarm_intelligence import ParticleSwarm, GreyWolf
from opt.benchmark.functions import shifted_ackley
import numpy as np
# Particle Swarm Optimization
pso = ParticleSwarm(
func=shifted_ackley,
lower_bound=-32.768,
upper_bound=32.768,
dim=10,
max_iter=100,
population_size=30
)
solution, fitness = pso.search()
print(f"PSO - Best fitness: {fitness:.6e}")
# Grey Wolf Optimizer
gwo = GreyWolf(
func=shifted_ackley,
lower_bound=-32.768,
upper_bound=32.768,
dim=10,
max_iter=100,
population_size=30
)
solution, fitness = gwo.search()
print(f"GWO - Best fitness: {fitness:.6e}")See Also
- Abstract Optimizer - Base class documentation
- Swarm Intelligence Algorithms - Algorithm details