Metaheuristic Algorithms API

API reference for metaheuristic algorithms in opt.metaheuristic.

Module Overview

from opt.metaheuristic import (
    HarmonySearch,
    CrossEntropy,
    SineCosine,
    TabuSearch,
    VariableNeighborhood,
)

Common Interface

class MetaheuristicAlgorithm(AbstractOptimizer):
    def __init__(
        self,
        func: Callable,
        lower_bound: float,
        upper_bound: float,
        dim: int,
        max_iter: int,
        **kwargs
    ):
        pass

    def search(self) -> tuple[np.ndarray, float]:
        pass

Available Algorithms

• HarmonySearch - Music-inspired optimization
• CrossEntropy - Adaptive importance sampling
• SineCosine - Mathematical function-based
• TabuSearch - Memory-based search
• VariableNeighborhood - Local search strategy

Example Usage

from opt.metaheuristic import HarmonySearch, SineCosine
from opt.benchmark.functions import ackley

# Harmony Search
hs = HarmonySearch(
    func=ackley,
    lower_bound=-32.768,
    upper_bound=32.768,
    dim=10,
    max_iter=100,
    harmony_memory_size=30,
    hmcr=0.9,  # Harmony memory consideration rate
    par=0.3    # Pitch adjustment rate
)
solution, fitness = hs.search()

# Sine Cosine Algorithm
sca = SineCosine(
    func=ackley,
    lower_bound=-32.768,
    upper_bound=32.768,
    dim=10,
    max_iter=100,
    population_size=30
)
solution, fitness = sca.search()

See Also

• Metaheuristic Algorithms - Algorithm details