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Copy pathbinpacking.cpp
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132 lines (113 loc) · 3.2 KB
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#include <iostream>
#include <vector>
#include <random>
template <class T>
void print_vector( std::vector<T> *vec )
{
std::cout << "{ ";
for( auto it = vec->begin(); it != vec->end(); ++it )
{
std::cout << *it;
if( (it + 1) != vec->end() )
{
std::cout << ",";
}
std::cout << " ";
}
std::cout << "}" << std::endl;
}
int best_fit( std::vector<float> *weights )
{
std::vector<float> bins;
bins.push_back( 0.0 );
bool found_bin;
auto best_bin = bins.begin();
for( auto weight_it = weights->begin(); weight_it != weights->end(); ++weight_it )
{
found_bin = false;
best_bin = bins.begin();
int bins_checked = 0;
for( auto bin_it = bins.begin(); bin_it != bins.end(); ++bin_it )
{
if( *bin_it + *weight_it <= 1.0 )
{
if( !found_bin || ( *bin_it + *weight_it ) >= ( *best_bin + *weight_it ) )
{
// bin is more full than previous best fit
best_bin = bin_it;
found_bin = true;
}
else
{
std::cout << "bin is not best" << std::endl;
}
}
++bins_checked;
}
std::cout << "checked " << bins_checked << " bins" << std::endl;
if( found_bin )
{
*best_bin = *best_bin + *weight_it;
}
else
{
// didn't find a bin, create a new one
bins.push_back( *weight_it );
}
print_vector( &bins );
}
print_vector( &bins );
return bins.size();
}
int worst_fit( std::vector<float> *weights )
{
std::vector<float> bins;
bins.push_back( 0.0 );
bool found_bin;
auto best_bin = bins.begin();
for( auto weight_it = weights->begin(); weight_it != weights->end(); ++weight_it )
{
found_bin = false;
best_bin = bins.begin();
for( auto bin_it = bins.begin(); bin_it != bins.end(); ++bin_it )
{
if( *bin_it + *weight_it <= 1.0 )
{
if( !found_bin || *bin_it <= *best_bin )
{
// bin is less full than best bin
best_bin = bin_it;
found_bin = true;
}
}
}
if( found_bin )
{
*best_bin = *best_bin + *weight_it;
}
else
{
// didn't find a bin, create a new one
bins.push_back( *weight_it );
}
print_vector( &bins );
}
print_vector( &bins );
return bins.size();
}
int main( int argv, char *argc[] )
{
std::random_device rd;
std::mt19937 gen( rd() );
std::uniform_real_distribution<> dist( 0.0, 1.0 );
std::vector<float> weights;
for( int i = 0; i < 20; ++i )
{
weights.push_back( dist( gen ) );
}
print_vector( &weights );
int n_bins = best_fit( &weights );
std::cout << "packed into " << n_bins << " using best-fit heuristic" << std::endl;
n_bins = worst_fit( &weights );
std::cout << "packed into " << n_bins << " using worst-fit heuristic" << std::endl;
}