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| .. | ||
| tests | ||
| __init__.py | ||
| greedy_knapsack.py | ||
| knapsack.py | ||
| README.md | ||
| recursive_approach_knapsack.py | ||
A naive recursive implementation of 0-1 Knapsack Problem
This overview is taken from:
https://en.wikipedia.org/wiki/Knapsack_problem
Overview
The knapsack problem is a problem in combinatorial optimization: Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as large as possible. It derives its name from the problem faced by someone who is constrained by a fixed-size knapsack and must fill it with the most valuable items. The problem often arises in resource allocation where the decision makers have to choose from a set of non-divisible projects or tasks under a fixed budget or time constraint, respectively.
The knapsack problem has been studied for more than a century, with early works dating as far back as 1897 The name "knapsack problem" dates back to the early works of mathematician Tobias Dantzig (1884–1956), and refers to the commonplace problem of packing the most valuable or useful items without overloading the luggage.
Documentation
This module uses docstrings to enable the use of Python's in-built help(...) function.
For instance, try help(Vector), help(unit_basis_vector), and help(CLASSNAME.METHODNAME).
Usage
Import the module knapsack.py from the . directory into your project.
Tests
. contains Python unit tests which can be run with python3 -m unittest -v.