About

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. The package provides tools to define (or randomly sample) knapsack instances, and generate useful metrics and visualisations.

I created this package as part of a research project. You can learn about me and my other projects by visiting my personal website.

Features

• Define and solve knapsack problem instances.

• 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)

Versioning

PyKP follows the Semantic Versioning standard.

License

PyKP is open-source software, licensed under the MIT License. See the LICENSE file on GitHub for details.