File Coverage

blib/lib/Algorithm/Knapsack.pm

Criterion	Covered	Total	%
statement	32	32	100.0
branch	6	6	100.0
condition			n/a
subroutine	6	6	100.0
pod	3	3	100.0
total	47	47	100.0

# $Id: Knapsack.pm,v 1.11 2004/10/23 18:52:19 alex Exp $

package Algorithm::Knapsack;

use strict;
use vars qw($VERSION);

$VERSION = '0.02';

=head1 NAME

Algorithm::Knapsack - brute-force algorithm for the knapsack problem

=head1 SYNOPSIS

    use Algorithm::Knapsack;

    my $knapsack = Algorithm::Knapsack->new(
        capacity => $capacity,
        weights  => \@weights,
    );

    $knapsack->compute();

    foreach my $solution ($knapsack->solutions()) {
        foreach my $index (@{$solution}) {
            # do something with $weights[$index]
        }
    }

=head1 DESCRIPTION

The knapsack problem asks, given a set of items of various weights, find a
subset or subsets of items such that their total weight is no larger than
some given capacity but as large as possible.

This module solves a special case of the 0-1 knapsack problem when the
value of each item is equal to its weight. Capacity and weights are
restricted to positive integers.

=head1 METHODS

=over 7

=item B

    my $knapsack = Algorithm::Knapsack->new(
        capacity => $capacity,
        weights  => \@weights,
    );

Creates a new Algorith::Knapsack object. Value of $capacity is a
positive integer and \@weights is a reference to an array of positive
integers, each of which is less than $capacity.

=cut

sub new {
    my $class = shift;
    my $self = {
        capacity    => 0,       # total capacity of this knapsack
        weights     => [],      # weights to be packed into the knapsack
        @_,
        solutions   => [],      # lol of indexes to weights
        emptiness   => 0,       # capacity minus sum of weights in a solution
    };
    bless $self, $class;
}

=item B

    $knapsack->compute();

Iterates over all possible combinations of weights to solve the knapsack
problem. Note that the time to solve the problem grows exponentially with
respect to the number of items (weights) to choose from.

=cut

sub compute {
    my $self = shift;
    $self->{emptiness} = $self->{capacity};
    $self->_knapsack($self->{capacity}, [0 .. $#{ $self->{weights} }], []);
}

sub _knapsack {
    my $self = shift;
    my $capacity = shift;
    my @indexes  = @{ shift() };
    my @knapsack = @{ shift() };

    while ($#indexes >= 0) {
        my $index = shift @indexes;
        next if $self->{weights}->[$index] > $capacity;

        if ($capacity - $self->{weights}->[$index] < $self->{emptiness}) {
            $self->{emptiness} = $capacity - $self->{weights}->[$index];
            $self->{solutions} = [];
        }
        if ($capacity - $self->{weights}->[$index] == $self->{emptiness}) {
            push(@{ $self->{solutions} }, [@knapsack, $index]);
        }

        $self->_knapsack($capacity - $self->{weights}->[$index],
                         \@indexes,
                         [@knapsack, $index]);
    }
}

=item B

    my @solutions = $knapsack->solutions();

Returns a list of solutions. Each solution is a reference to an array of
indexes to @weights.

=cut

sub solutions {
    my $self = shift;
    return @{ $self->{solutions} };
}

1;

__END__