Maximal Packing of a Knapsack with Given Items

**KNAPSACK_01**,
a Python library which
uses brute force to solve small versions of the 0/1 knapsack problem.

In the 0/1 knapsack problem, we are given a knapsack with carrying capacity C, and a set of N items, with the I-th item having a weight of W(I). We want to pack as much total weight as possible into the knapsack without exceeding the weight limit. We do this by specifying which items we will not take (0) or take (1).

This library uses a simple brute force or exhaustive search method, which is guaranteed to get the optimal solution, but which is not efficient for large values of N.

The computer code and data files described and made available on this web page are distributed under the GNU LGPL license.

**KNAPSACK_01** is available in
a C version and
a C++ version and
a FORTRAN90 version and
a MATLAB version and
a Python version.

KNAPSACK_01, a dataset directory which contains test data for the 0/1 knapsack problem;

PARTITION_PROBLEM, a Python library which seeks solutions of the partition problem, splitting a set of integers into two subsets with equal sum.

SATISFY, a Python program which demonstrates, for a particular circuit, an exhaustive search for solutions of the circuit satisfiability problem.

SUBSET, a Python library which enumerates, generates, ranks and unranks combinatorial objects including combinations, partitions, subsets, index sets, and trees.

SUBSET_SUM, a Python library which seeks solutions of the subset sum problem, in which it is desired to find a subset of a set of integers which has a given sum.

- knapsack_01_brute.py seeks the optimal solution of the 0/1 knapsack problem using exhaustive search.
- subset_gray_next.py computes all possible subsets of a set of N objects, one at a time.
- timestamp.py prints the current YMDHMS date as a time stamp.

- knapsack_01_test.py, calls all the tests.
- knapsack_01_test.sh, runs all the tests.
- knapsack_01_test.txt, the output file.

You can go up one level to the Python source codes.