PyKP

Sample, solve, and analyse instances of the 0-1 Knapsack Problem.

PyKP (py·kay·pee) is a Python package for defining, solving, and analysing knapsack problem instances. This package provides tools to set up knapsacks, and generate useful metrics and visualisations. Additionally, it includes a sampling feature that generates knapsack instances based on defined distributions.

Features

  • Define knapsack problem instances.

  • Solve knapsack problems efficiently.

  • Analyse computational complexity metrics.

  • Randomly sample knapsack instances based on distribution parameters.

  • Visualise knapsack instances and solutions.

Quick Start

Here’s a quick example to get started with PyKP:

from pykp import Knapsack
from pykp import Item

# Define knapsack items
items = [
    Item(value=10, weight=5),
    Item(value=15, weight=10),
    Item(value=7, weight=3)
]

# Initialise and solve a knapsack problem
capacity = 15
knapsack = Knapsack(items=items, capacity=capacity)
knapsack.solve()

# Print the optimal solution
print("Optimal solution value:", knapsack.optimal_nodes[0].value)

Explore

Documentation