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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01//EN"
"http://www.w3.org/TR/html4/strict.dtd">
<html>
<head>
<title>Combinations and Permutations</title>
<style type="text/css">
p {text-align:justify}
li {text-align:justify}
blockquote.note
{
background-color:#E0E0E0;
padding-left: 15px;
padding-right: 15px;
padding-top: 1px;
padding-bottom: 1px;
}
ins {background-color:#A0FFA0}
del {background-color:#FFA0A0}
</style>
</head>
<body>
<address align=right>
Document number: Dxxxx=xx-xxxx<br>
<br>
<a href="mailto:[email protected]">Howard Hinnant</a><br>
2011-02-12
</address>
<hr>
<h1 align="center">Combinations and Permutations</h1>
<h2>Introduction</h2>
<p>
It doesn't happen very often, but every once in awhile one needs to iterate over
all of the combinations or permutations of a set of objects. Or more
specifically, given a set of <tt>N</tt> objects, you want to consider <tt>r</tt>
of them at a time (for each combination or permutation). The standard library
offers <tt>next_permutation</tt>, but this offering alone has a few drawbacks:
</p>
<ul>
<li>
<tt>next_permutation</tt> only offers permutations of <tt>N</tt> objects taken
<tt>N</tt> at a time. If you only need to consider permutations of length
<tt>r</tt> chosen from a list of length <tt>N</tt> then you can save a factor of
<tt>(n-r)!</tt> by iterating over only the permutations you need. If <tt>r</tt>
is small compared to <tt>N</tt> this can easily be several orders of magnitude
faster than iterating over all <tt>N!</tt> permutations.
</li>
<li>
If one only needs permutations, but not the reverse permutation, a factor
of 2 can be saved by iterating only over reversible permutations.
</li>
<li>
If your permutations are of a circular nature, you can save a factor of <tt>r</tt>
by iterating over only distinct circular permutations.
</li>
<li>
If your permutations are of a circular nature <em>and</em> it doesn't matter
whether your permutation goes in a clockwise or counter-clockwise direction,
then iterating only over distinct reversible, circular permutations can save
a factor of <tt>2r</tt> iterations compared to iterating over all <tt>N!</tt>
permutations.
</li>
<li>
If you're examining permutations of length <tt>r</tt> out of a list of length
<tt>N</tt> and order doesn't matter at all in each list of length <tt>r</tt>,
then it is far cheaper to iterate only over combinations of the <tt>N</tt>
items taken <tt>r</tt> at a time (by a factor of <tt>r!</tt>).
</li>
<li>
The user interface of <tt>next_permutation</tt> is potentially expensive:
for each iteration the algorithm must do a search for the next iteration. When
iterating <tt>N</tt> items taken <tt>r</tt> at a time, and when the number of
iterations is far less than <tt>N!</tt> (as it will be for many practical
problems), then the time spent finding the next iteration using a
<tt>next_permutation</tt>-style interface can completely swamp the time you
spend actually visiting each permutation.
</li>
<li>
To use <tt>next_permutation</tt>, the sequence must be LessThanComparable
and in sorted order.
</li>
</ul>
<p>
Below is a solution to each of these problems and more. The following generic
algorithms permit a client to visit every combination or permuation of a
sequence of length <tt>N</tt>, <tt>r</tt> items at time.
</p>
<blockquote><pre>
template <class BidirIter, class Function>
Function
<b>for_each_permutation</b>(BidirIter first,
BidirIter mid,
BidirIter last,
Function f);
template <class BidirIter, class Function>
Function
<b>for_each_reversible_permutation</b>(BidirIter first,
BidirIter mid,
BidirIter last,
Function f);
template <class BidirIter, class Function>
Function
<b>for_each_circular_permutation</b>(BidirIter first,
BidirIter mid,
BidirIter last,
Function f);
template <class BidirIter, class Function>
Function
<b>for_each_reversible_circular_permutation</b>(BidirIter first,
BidirIter mid,
BidirIter last,
Function f);
template <class BidirIter, class Function>
Function
<b>for_each_combination</b>(BidirIter first,
BidirIter mid,
BidirIter last,
Function f);
</pre></blockquote>
<p>
These each follow a <tt>for_each</tt> style: The algorithm calls a user
supplied function object for each combination/permutation in the sequence:
<tt>f(begin, end)</tt>. That function object can of course maintain state. The
sequence need not be sorted, nor even contain unique objects. The algorithms do
not consider the value of the sequence elements at all. That is, the element
type need not support <tt>LessThanComparable</tt> nor
<tt>EqualityComparable</tt>. Furthermore the algorithms follow three additional
rules:
</p>
<ol>
<li>
On normal (non-exceptional) completion, the sequence is always left in the
original order.
</li>
<li>
<p>
The functor is always called with <tt>[first, mid)</tt>. This enables the
functor to also access the elements not in the sequence if it is aware of the
sequence: <tt>[mid, last)</tt>. This can come in handy when dealing
with nested combination/permutation problems where for each permutation you
<em>also</em> need to compute combinations and/or permutations on those elements
<em>not</em> selected.
</p>
</li>
<li>
<p>
The functor should return <tt>true</tt> or <tt>false</tt>:
</p>
<ul>
<li>
<tt>true</tt> if the functor wishes to break out of the <tt>for_each_</tt> loop.
</li>
<li>
Otherwise <tt>false</tt>.
</li>
</ul>
</li>
</ol>
<p>
The following generic algorithms take a (preferably unsigned) integral type and
return the number of combinations or permutations that exist. Traditionally
these functions represent functions such as <tt><sub>n</sub>C<sub>r</sub></tt>
and <tt><sub>n</sub>P<sub>r</sub></tt>. This API breaks with tradition
concerning the definition of <tt>n</tt>. These functions compute:
<tt><sub>d1+d2</sub>C<sub>d1</sub></tt>, and
<tt><sub>d1+d2</sub>P<sub>d1</sub></tt>, and the related variations for
reversible and circular permuations. The rationale for this API is to mesh
well with the aforementioned <tt>for_each_*</tt> algorithms. <tt>d1</tt> is
<tt>distance(first, mid)</tt> and <tt>d2</tt> is <tt>distance(mid, last)</tt>.
</p>
<blockquote><pre>
template <class UInt>
UInt
<b>count_each_combination</b>(UInt d1, UInt d2);
template <class UInt>
UInt
<b>count_each_permutation</b>(UInt d1, UInt d2);
template <class UInt>
UInt
<b>count_each_circular_permutation</b>(UInt d1, UInt d2);
template <class UInt>
UInt
<b>count_each_reversible_permutation</b>(UInt d1, UInt d2);
template <class UInt>
UInt
<b>count_each_reversible_circular_permutation</b>(UInt d1, UInt d2);
</pre></blockquote>
<p>
Each of the above algorithms avoids intermediate overflow. That is, if the
final answer is representable as a <tt>UInt</tt>, then they will return the
correct answer. Otherwise they will throw a <tt>std::overflow_error</tt>. This
noisy overflow protection is necessary as these functions can easily overflow.
For example <tt>count_each_combination(33ull, 34ull)</tt> returns
14,226,520,737,620,288,370. But
<tt>count_each_combination(33ull, 35ull)</tt> overflows for a 64 bit
<tt>unsigned long long</tt>. Without overflow protection, the returned result
will look quite reasonable to the casual observer and overflow is likely to
happen accidentally, go unnoticed, and cause further problems in program logic
which will be more difficult to diagnose.
</p>
<p>
Furthermore the following convenience functions are provided in order to more
easily "preflight" ranges sent to the <tt>for_each_*</tt> algorithms. The
reason that the <tt>UInt</tt> overloads of these algorithms exist is so that you
don't <em>have</em> to create a range to compute
<tt><sub>3000</sub>C<sub>2</sub></tt>. Instead you can simply call
<tt>count_each_combination(2ull, 2998ull)</tt> (for example).
</p>
<blockquote><pre>
template <class BidirIter>
std::uintmax_t
<b>count_each_combination</b>(BidirIter first,
BidirIter mid,
BidirIter last);
template <class BidirIter>
std::uintmax_t
<b>count_each_permutation</b>(BidirIter first,
BidirIter mid,
BidirIter last);
template <class BidirIter>
std::uintmax_t
<b>count_each_circular_permutation</b>(BidirIter first,
BidirIter mid,
BidirIter last);
template <class BidirIter>
std::uintmax_t
<b>count_each_reversible_permutation</b>(BidirIter first,
BidirIter mid,
BidirIter last);
template <class BidirIter>
std::uintmax_t
<b>count_each_reversible_circular_permutation</b>(BidirIter first,
BidirIter mid,
BidirIter last);
</pre></blockquote>
<h2>Examples</h2>
<p>
Below an example simply fills a vector with consecutive integers, and calls
<tt>for_each_permutation</tt> on a functor that will print out the permutation.
The functor will also print out items not in the permutation after a trailing
<tt>'|'</tt>. The functor also counts the number of permutations visited so
that the client can query that amount after the call to
<tt>for_each_permutation</tt>.
</p>
<blockquote><pre>
#include <iostream>
#include <vector>
#include <numeric>
#include <cstdint>
#include <cassert>
<font color="#C80000">// print out a range separated by commas,</font>
<font color="#C80000">// return number of values printed.</font>
template <class It>
unsigned
display(It begin, It end)
{
unsigned r = 0;
if (begin != end)
{
std::cout << *begin;
++r;
for (++begin; begin != end; ++begin)
{
std::cout << ", " << *begin;
++r;
}
}
return r;
}
<font color="#C80000">// functor called for each permutation</font>
class f
{
unsigned len;
std::uint64_t count;
public:
explicit f(unsigned l) : len(l), count(0) {}
template <class It>
<b>bool operator()(It first, It last)</b> <font color="#C80000">// called for each permutation</font>
{
<font color="#C80000">// count the number of times this is called</font>
++count;
<font color="#C80000">// print out [first, mid) surrounded with [ ... ]</font>
std::cout << "[ ";
unsigned r = display(first, last);
<font color="#C80000">// If [mid, last) is not empty, then print it out too</font>
<font color="#C80000">// prefixed by " | "</font>
if (r < len)
{
std::cout << " | ";
display(last, std::next(last, len - r));
}
std::cout << " ]\n";
return false;
}
operator std::uint64_t() const {return count;}
};
int main()
{
const int r = 3;
const int n = 5;
std::vector<int> v(n);
std::iota(v.begin(), v.end(), 0);
std::uint64_t count = <b>for_each_permutation(v.begin(),
v.begin() + r,
v.end(),
f(v.size()));</b>
<font color="#C80000">// print out "---" to the correct length for the above output</font>
unsigned e = 3 * r + 2;
if (r < v.size())
e += 1 + 3 * (v.size() - r);
for (unsigned i = 0; i < e; ++i)
std::cout << '-';
<font color="#C80000">// print out the permuted vector to show that it has the original order</font>
std::cout << "\n[ ";
display(v.begin(), v.end());
std::cout << " ]\n";
<font color="#C80000">// sanity check</font>
assert(count == <b>count_each_permutation(v.begin(), v.begin() + r, v.end()));</b>
<font color="#C80000">// print out summary of what has happened,</font>
<font color="#C80000">// using 'count' from functor state returned from for_each_permutation algorithm.</font>
std::cout << "Found " << count << " permutations of " << v.size()
<< " objects taken " << r << " at a time.\n";
}
</pre></blockquote>
<p>
And this is the output of this program:
</p>
<blockquote><pre>
[ 0, 1, 2 | 3, 4 ]
[ 0, 2, 1 | 3, 4 ]
[ 1, 0, 2 | 3, 4 ]
[ 1, 2, 0 | 3, 4 ]
[ 2, 0, 1 | 3, 4 ]
[ 2, 1, 0 | 3, 4 ]
[ 0, 1, 3 | 2, 4 ]
[ 0, 3, 1 | 2, 4 ]
[ 1, 0, 3 | 2, 4 ]
[ 1, 3, 0 | 2, 4 ]
[ 3, 0, 1 | 2, 4 ]
[ 3, 1, 0 | 2, 4 ]
[ 0, 1, 4 | 2, 3 ]
[ 0, 4, 1 | 2, 3 ]
[ 1, 0, 4 | 2, 3 ]
[ 1, 4, 0 | 2, 3 ]
[ 4, 0, 1 | 2, 3 ]
[ 4, 1, 0 | 2, 3 ]
[ 0, 2, 3 | 1, 4 ]
[ 0, 3, 2 | 1, 4 ]
[ 2, 0, 3 | 1, 4 ]
[ 2, 3, 0 | 1, 4 ]
[ 3, 0, 2 | 1, 4 ]
[ 3, 2, 0 | 1, 4 ]
[ 0, 2, 4 | 1, 3 ]
[ 0, 4, 2 | 1, 3 ]
[ 2, 0, 4 | 1, 3 ]
[ 2, 4, 0 | 1, 3 ]
[ 4, 0, 2 | 1, 3 ]
[ 4, 2, 0 | 1, 3 ]
[ 0, 3, 4 | 1, 2 ]
[ 0, 4, 3 | 1, 2 ]
[ 3, 0, 4 | 1, 2 ]
[ 3, 4, 0 | 1, 2 ]
[ 4, 0, 3 | 1, 2 ]
[ 4, 3, 0 | 1, 2 ]
[ 1, 2, 3 | 0, 4 ]
[ 1, 3, 2 | 0, 4 ]
[ 2, 1, 3 | 0, 4 ]
[ 2, 3, 1 | 0, 4 ]
[ 3, 1, 2 | 0, 4 ]
[ 3, 2, 1 | 0, 4 ]
[ 1, 2, 4 | 0, 3 ]
[ 1, 4, 2 | 0, 3 ]
[ 2, 1, 4 | 0, 3 ]
[ 2, 4, 1 | 0, 3 ]
[ 4, 1, 2 | 0, 3 ]
[ 4, 2, 1 | 0, 3 ]
[ 1, 3, 4 | 0, 2 ]
[ 1, 4, 3 | 0, 2 ]
[ 3, 1, 4 | 0, 2 ]
[ 3, 4, 1 | 0, 2 ]
[ 4, 1, 3 | 0, 2 ]
[ 4, 3, 1 | 0, 2 ]
[ 2, 3, 4 | 0, 1 ]
[ 2, 4, 3 | 0, 1 ]
[ 3, 2, 4 | 0, 1 ]
[ 3, 4, 2 | 0, 1 ]
[ 4, 2, 3 | 0, 1 ]
[ 4, 3, 2 | 0, 1 ]
------------------
[ 0, 1, 2, 3, 4 ]
Found 60 permutations of 5 objects taken 3 at a time.
</pre></blockquote>
<p>
The above list can be cut in half by instead calling:
</p>
<blockquote><pre>
for_each_reversible_permutation(v.begin(), v.begin() + r, v.end(), f(v.size()));
[ 0, 1, 2 | 3, 4 ]
[ 0, 2, 1 | 3, 4 ]
[ 1, 0, 2 | 3, 4 ]
[ 0, 1, 3 | 2, 4 ]
[ 0, 3, 1 | 2, 4 ]
[ 1, 0, 3 | 2, 4 ]
[ 0, 1, 4 | 2, 3 ]
[ 0, 4, 1 | 2, 3 ]
[ 1, 0, 4 | 2, 3 ]
[ 0, 2, 3 | 1, 4 ]
[ 0, 3, 2 | 1, 4 ]
[ 2, 0, 3 | 1, 4 ]
[ 0, 2, 4 | 1, 3 ]
[ 0, 4, 2 | 1, 3 ]
[ 2, 0, 4 | 1, 3 ]
[ 0, 3, 4 | 1, 2 ]
[ 0, 4, 3 | 1, 2 ]
[ 3, 0, 4 | 1, 2 ]
[ 1, 2, 3 | 0, 4 ]
[ 1, 3, 2 | 0, 4 ]
[ 2, 1, 3 | 0, 4 ]
[ 1, 2, 4 | 0, 3 ]
[ 1, 4, 2 | 0, 3 ]
[ 2, 1, 4 | 0, 3 ]
[ 1, 3, 4 | 0, 2 ]
[ 1, 4, 3 | 0, 2 ]
[ 3, 1, 4 | 0, 2 ]
[ 2, 3, 4 | 0, 1 ]
[ 2, 4, 3 | 0, 1 ]
[ 3, 2, 4 | 0, 1 ]
------------------
[ 0, 1, 2, 3, 4 ]
Found 30 permutations of 5 objects taken 3 at a time.
</pre></blockquote>
<p>
For example <tt>[ 2, 1, 0 ]</tt> is not found in the above list.
</p>
<p>
By instead calling:
</p>
<blockquote><pre>
for_each_circular_permutation(v.begin(), v.begin() + r, v.end(), f(v.size()));
</pre></blockquote>
<p>
the original list can be cut by a third:
</p>
<blockquote><pre>
[ 0, 1, 2 | 3, 4 ]
[ 0, 2, 1 | 3, 4 ]
[ 0, 1, 3 | 2, 4 ]
[ 0, 3, 1 | 2, 4 ]
[ 0, 1, 4 | 2, 3 ]
[ 0, 4, 1 | 2, 3 ]
[ 0, 2, 3 | 1, 4 ]
[ 0, 3, 2 | 1, 4 ]
[ 0, 2, 4 | 1, 3 ]
[ 0, 4, 2 | 1, 3 ]
[ 0, 3, 4 | 1, 2 ]
[ 0, 4, 3 | 1, 2 ]
[ 1, 2, 3 | 0, 4 ]
[ 1, 3, 2 | 0, 4 ]
[ 1, 2, 4 | 0, 3 ]
[ 1, 4, 2 | 0, 3 ]
[ 1, 3, 4 | 0, 2 ]
[ 1, 4, 3 | 0, 2 ]
[ 2, 3, 4 | 0, 1 ]
[ 2, 4, 3 | 0, 1 ]
------------------
[ 0, 1, 2, 3, 4 ]
Found 20 permutations of 5 objects taken 3 at a time.
</pre></blockquote>
<p>
For example you will not find the following in the above list:
</p>
<blockquote><pre>
[ 1, 2, 0 ] // rotate(0, 1, 3) of permutation 1
[ 2, 0, 1 ] // rotate(0, 2, 3) of permutation 1
</pre></blockquote>
<p>
And if your circular permutations are also reversible, your list (and time
spent) can be halved again:
</p>
<blockquote><pre>
for_each_reversible_circular_permutation(v.begin(), v.begin() + r, v.end(), f(v.size()));
[ 0, 1, 2 | 3, 4 ]
[ 0, 1, 3 | 2, 4 ]
[ 0, 1, 4 | 2, 3 ]
[ 0, 2, 3 | 1, 4 ]
[ 0, 2, 4 | 1, 3 ]
[ 0, 3, 4 | 1, 2 ]
[ 1, 2, 3 | 0, 4 ]
[ 1, 2, 4 | 0, 3 ]
[ 1, 3, 4 | 0, 2 ]
[ 2, 3, 4 | 0, 1 ]
------------------
[ 0, 1, 2, 3, 4 ]
Found 10 permutations of 5 objects taken 3 at a time.
</pre></blockquote>
<p>
For example you will not find the following in the above list:
</p>
<blockquote><pre>
[ 2, 1, 0 ] // reverse(0, 3) of permutation(1)
[ 1, 2, 0 ] // rotate(0, 1, 3) of permutation(1)
[ 0, 2, 1 ] // reverse of rotate(0, 1, 3) of permutation(1)
[ 2, 0, 1 ] // rotate(0, 2, 3) of permutation(1)
[ 1, 0, 2 ] // reverse of rotate(0, 2, 3) of permutation(1)
</pre></blockquote>
<p>
When <tt>r</tt> is 3 or less, then reversible circular permutations are the
exact same as combinations. In this case use of <tt>for_each_combination</tt>
should be preferred as it will be a little more efficient. Additionally when
<tt>r</tt> is 2 or less, <tt>for_each_combination</tt> produces the same result
as <tt>for_each_circular_permutation</tt> and
<tt>for_each_reversible_permutation</tt>. When <tt>r == 1</tt>, all five
algorithms produce the same <tt>N</tt> permutations. When <tt>r == 0</tt>, all
five algorithms call the functor once with the empty range <tt>[first,
mid)</tt>.
</p>
<h3>A more complex example</h3>
<p>
You may be wondering: when would I ever need to use any of this stuff in a
real world example?
</p>
<p>
Wikipedia documents a real-world problems such as the
<a href="http://en.wikipedia.org/wiki/Cutting_stock_problem#Illustration_of_one-dimensional_cutting-stock_problem">cutting-stock problem</a>.
The idea is to optimally cut a long roll of paper to meet customers orders of
varying length and quantity of rolls. While the complete solution is outside of
the scope of this paper, these algorithms can easily be used for parts of this
problem. For example the article gives a specific problem and lets us know that
there are 308 possible ways to cut the roll, some of which can be chosen to
meet the customer's orders. <tt>for_each_combination</tt> can be easily used
to enumerate those 308 possibilities in the following code.
</p>
<blockquote><pre>
#include <iostream>
#include <vector>
#include <numeric>
#include <map>
<font color="#C80000">// collect unique solutions</font>
struct cost
{
std::map<std::vector<int>, int> set_;
bool
operator()(int* first, int* last)
{
if (first != last)
{
int len = std::accumulate(first, last, 0);
if (len <= 5600) <font color="#C80000">// do not collect non-solutions</font>
{
std::vector<int> s(first, last);
std::sort(s.begin(), s.end());
<font color="#C80000">// reject duplicate solutions</font>
set_.insert(std::make_pair(s, 5600-len));
}
}
return false;
}
};
int main()
{
int widths[] = {1380, 1380, 1380, 1380, 1520, 1520, 1520, 1560, 1560, 1560,
1710, 1710, 1710, 1820, 1820, 1820, 1880, 1880, 1930, 1930,
2000, 2000, 2050, 2050, 2100, 2100, 2140, 2140, 2150, 2150,
2200, 2200};
int N = sizeof(widths)/sizeof(widths[0]);
<font color="#C80000">// Collect solutions of lengths 1 - 4. Other solutions are not possible</font>
cost c = for_each_combination(widths, widths+1, widths+N, cost());
c = for_each_combination(widths, widths+2, widths+N, std::move(c));
c = for_each_combination(widths, widths+3, widths+N, std::move(c));
c = for_each_combination(widths, widths+4, widths+N, std::move(c));
<font color="#C80000">// Sort the solutions by waste</font>
std::multimap<int, std::vector<int> > mm;
for (std::map<std::vector<int>, int>::iterator i = c.set_.begin(); i != c.set_.end(); ++i)
mm.insert(std::make_pair(i->second, i->first));
<font color="#C80000">// Output solutions</font>
for (std::multimap<int, std::vector<int> >::iterator i = mm.begin(); i != mm.end(); ++i)
{
std::cout << *i->second.begin();
if (i->second.size() > 1)
{
for (std::vector<int>::const_iterator j = i->second.begin()+1; j != i->second.end(); ++j)
std::cout << ", " << *j;
}
std::cout << ": waste = " << i->first << '\n';
}
}
</pre></blockquote>
<p>
The output is 308 lines long:
</p>
<blockquote><pre>
1520, 1880, 2200: waste = 0
1520, 1930, 2150: waste = 0
1520, 1930, 2140: waste = 10
1560, 1880, 2150: waste = 10
1560, 1930, 2100: waste = 10
1710, 1880, 2000: waste = 10
1380, 2000, 2200: waste = 20
1380, 2050, 2150: waste = 20
1380, 2100, 2100: waste = 20
1560, 1820, 2200: waste = 20
1560, 1880, 2140: waste = 20
1710, 1820, 2050: waste = 20
1820, 1880, 1880: waste = 20
1380, 2050, 2140: waste = 30
1520, 2000, 2050: waste = 30
1710, 1710, 2150: waste = 30
1710, 1930, 1930: waste = 30
1820, 1820, 1930: waste = 30
1560, 2000, 2000: waste = 40
1710, 1710, 2140: waste = 40
1520, 1880, 2150: waste = 50
1520, 1930, 2100: waste = 50
1520, 1820, 2200: waste = 60
1520, 1880, 2140: waste = 60
1560, 1880, 2100: waste = 60
1560, 1930, 2050: waste = 60
1380, 2000, 2150: waste = 70
1380, 2050, 2100: waste = 70
1560, 1820, 2150: waste = 70
1710, 1820, 2000: waste = 70
1380, 1380, 1380, 1380: waste = 80
1380, 2000, 2140: waste = 80
...
2200, 2200: waste = 1200
2150, 2200: waste = 1250
2140, 2200: waste = 1260
1380, 1380, 1560: waste = 1280
2100, 2200: waste = 1300
2150, 2150: waste = 1300
2140, 2150: waste = 1310
1380, 1380, 1520: waste = 1320
2140, 2140: waste = 1320
2050, 2200: waste = 1350
2100, 2150: waste = 1350
...
2200: waste = 3400
2150: waste = 3450
2140: waste = 3460
2100: waste = 3500
2050: waste = 3550
2000: waste = 3600
1930: waste = 3670
1880: waste = 3720
1820: waste = 3780
1710: waste = 3890
1560: waste = 4040
1520: waste = 4080
1380: waste = 4220
</pre></blockquote>
<p>
Obviously this isn't a final solution to the cutting-stock problem. However it
is an important and instructive intermediate step. The subsequent steps
(including finding the minimum number of knife changes) involve searching
permutations - the order of the cutting patterns, and the order of the cuts in
each pattern.
</p>
<h2>Performance Considerations</h2>
<p>
<img align="right" hspace="10" vspace="10" height="800" src="fig1.tiff"/>
</p>
<p>
Hervé Brönnimann published
<a href="http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2008/n2639.pdf">N2639</a>
proposing functionality somewhat similar as to what is outlined herein,
including:
</p>
<blockquote><pre>
template <class BidirIter>
bool
next_partial_permutation(BidirIter first,
BidirIter mid,
BidirIter last);
template <class BidirIter >
bool
next_combination(BidirIter first,
BidirIter mid,
BidirIter last);
</pre></blockquote>
<p>
This interface follows the style of the existing <tt>std::next_permutation</tt>
algorithm. It is the inverse of the <tt>for_each</tt> style: The client calls
the functor directly, and then calls the algorithm to find the next iteration.
</p>
<p>
The problem with this interface is that it can get expensive to find the next
iteration. For example when calling <tt>for_each_permutation</tt> and
<tt>next_partial_permutation</tt> with <tt>r == 4</tt> and varying <tt>N</tt>
from 4 to 100, the time to iterate through the permutations skyrockets for
<tt>next_partial_permutation</tt>, but not for <tt>for_each_permutation</tt>.
By the time <tt>N == 100</tt>, <tt>for_each_permutation</tt> is running nearly
45 times faster than <tt>next_partial_permutation</tt>, taking 20 seconds to
do what <tt>for_each_permutation</tt> is accomplishing in under half a second.
This trend rapidly gets worse as <tt>N</tt> grows.
</p>
<p>
The same performance comparison can be made between <tt>next_combination</tt>
and <tt>for_each_combination</tt>. It should be stressed that this isn't a lack
of quality or care put into the
<a href="http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2008/n2639.pdf">N2639</a>
implementation. I've studied that implementation carefully and consider it very
high quality. It is simply that the number of comparisons that need to be done
to find out which swaps need to be done gets outrageously expensive. The number
of swaps actually performed in both algorithms is approximately the same. In the
case of combinations, <tt>N</tt> has to grow much higher before the iteration
time starts to swamp the algorithm, but that is because the number of generated
permutations is low with combinations, compared to permutations. At <tt>N ==
4000</tt> <tt>for_each_combination</tt> is running well over 1000 times faster
than <tt>next_combination</tt>.
</p>
<p>
If the <tt>next_*</tt> algorithms are to be put to use, it should be made clear that
these algorithms should <em>only</em> be employed when it is expected that the client
code will break out of the loop early. When it is expected that all
permutations will be visited then the <tt>for_each</tt> algorithms are
<em>always</em> faster, often orders of magnitude so.
</p>
<h2>Synopsis</h2>
<blockquote><pre>
<font color="#C80000">// Integral-based count_each_*</font>
template <class UInt>
UInt
count_each_permutation(UInt d1, UInt d2);
template <class UInt>
UInt
count_each_reversible_permutation(UInt d1, UInt d2);
template <class UInt>
UInt
count_each_circular_permutation(UInt d1, UInt d2);
template <class UInt>
UInt
count_each_reversible_circular_permutation(UInt d1, UInt d2);
template <class UInt>
UInt
count_each_combination(UInt d1, UInt d2);
<font color="#C80000">// Iterator-based count_each_*</font>
template <class BidirIter>
std::uintmax_t
count_each_permutation(BidirIter first,
BidirIter mid,
BidirIter last);
template <class BidirIter>
std::uintmax_t
count_each_reversible_permutation(BidirIter first,
BidirIter mid,
BidirIter last);
template <class BidirIter>
std::uintmax_t
count_each_circular_permutation(BidirIter first,
BidirIter mid,
BidirIter last);
template <class BidirIter>
std::uintmax_t
count_each_reversible_circular_permutation(BidirIter first,
BidirIter mid,
BidirIter last);
template <class BidirIter>
std::uintmax_t
count_each_combination(BidirIter first,
BidirIter mid,
BidirIter last);
<font color="#C80000">// Iterator-based for_each_* algorithms</font>
template <class BidirIter, class Function>
Function
for_each_permutation(BidirIter first,
BidirIter mid,
BidirIter last,
Function f);
template <class BidirIter, class Function>
Function
for_each_reversible_permutation(BidirIter first,
BidirIter mid,
BidirIter last,
Function f);
template <class BidirIter, class Function>
Function
for_each_circular_permutation(BidirIter first,
BidirIter mid,
BidirIter last,
Function f);
template <class BidirIter, class Function>
Function
for_each_reversible_circular_permutation(BidirIter first,
BidirIter mid,
BidirIter last,
Function f);
template <class BidirIter, class Function>
Function
for_each_combination(BidirIter first,
BidirIter mid,
BidirIter last,
Function f);
</pre></blockquote>
<h2>Specification</h2>
<p>
<i>Remarks:</i> In this section a post-fix <tt>!</tt> indicates a
<a href="http://en.wikipedia.org/wiki/Factorial">factorial operator</a> and has
higher precedence than any other operator.
</p>
<blockquote><pre>
template <class UInt>
UInt
count_each_permutation(UInt d1, UInt d2);
</pre>
<blockquote>
<p>
<i>Requires:</i> <tt>Uint</tt> is an integral type or a type emulating an
integral type. If <tt>Uint</tt> is a signed integral type (or emulation of a
signed integral type), then <tt>d1</tt> and <tt>d2</tt> are non-negative.
</p>
<p>
<i>Returns:</i> <tt>(d1 + d2)!/d2!</tt>.
</p>
<p>
<i>Throws:</i> If the computed value is not representable in the type
<tt>UInt</tt>, throws <tt>std::overflow_error</tt>.
</p>
<p>
<i>Remarks:</i> If the computed value is representable in the type
<tt>UInt</tt>, returns the correct value. This algorithm avoids intermediate
overflow.
</p>
</blockquote>
</blockquote>
<blockquote><pre>
template <class UInt>
UInt
count_each_reversible_permutation(UInt d1, UInt d2);
</pre>
<blockquote>
<p>
<i>Requires:</i> <tt>Uint</tt> is an integral type or a type emulating an
integral type. If <tt>Uint</tt> is a signed integral type (or emulation of a
signed integral type), then <tt>d1</tt> and <tt>d2</tt> are non-negative.
</p>
<p>
<i>Returns:</i> If <tt>d1 <= 1</tt> returns <tt>(d1 + d2)!/d2!</tt>. Else
returns <tt>(d1 + d2)!/(2*(d2!))</tt>.
</p>
<p>
<i>Throws:</i> If the computed value is not representable in the type
<tt>UInt</tt>, throws <tt>std::overflow_error</tt>.
</p>
<p>
<i>Remarks:</i> If the computed value is representable in the type
<tt>UInt</tt>, returns the correct value. This algorithm avoids intermediate
overflow.
</p>
</blockquote>
</blockquote>
<blockquote><pre>
template <class UInt>
UInt
count_each_circular_permutation(UInt d1, UInt d2);
</pre>
<blockquote>
<p>
<i>Requires:</i> <tt>Uint</tt> is an integral type or a type emulating an
integral type. If <tt>Uint</tt> is a signed integral type (or emulation of a
signed integral type), then <tt>d1</tt> and <tt>d2</tt> are non-negative.
</p>
<p>
<i>Returns:</i> If <tt>d1 == 0</tt> returns 1. Else returns <tt>(d1 +
d2)!/(d1*(d2!))</tt>.
</p>
<p>
<i>Throws:</i> If the computed value is not representable in the type
<tt>UInt</tt>, throws <tt>std::overflow_error</tt>.
</p>
<p>
<i>Remarks:</i> If the computed value is representable in the type
<tt>UInt</tt>, returns the correct value. This algorithm avoids intermediate
overflow.
</p>
</blockquote>
</blockquote>
<blockquote><pre>
template <class UInt>
UInt
count_each_reversible_circular_permutation(UInt d1, UInt d2);
</pre>
<blockquote>
<p>
<i>Requires:</i> <tt>Uint</tt> is an integral type or a type emulating an
integral type. If <tt>Uint</tt> is a signed integral type (or emulation of a
signed integral type), then <tt>d1</tt> and <tt>d2</tt> are non-negative.
</p>