# Permutation

In mathematics, a **permutation** of a set is, loosely speaking, an arrangement of its members into a sequence or linear order, or if the set is already ordered, a rearrangement of its elements. The word "permutation" also refers to the act or process of changing the linear order of an ordered set.^{[1]}

Permutations are used in almost every branch of mathematics, and in many other fields of science. In computer science, they are used for analyzing sorting algorithms; in quantum physics, for describing states of particles; and in biology, for describing RNA sequences.

The number of permutations of *n* distinct objects is *n* factorial, usually written as *n*!, which means the product of all positive integers less than or equal to *n*.

In elementary combinatorics, the *k*-permutations, or partial permutations, are the ordered arrangements of *k* distinct elements selected from a set. When *k* is equal to the size of the set, these are the permutations of the set.

Permutations called hexagrams were used in China in the I Ching (Pinyin: Yi Jing) as early as 1000 BC.

Al-Khalil (717–786), an Arab mathematician and cryptographer, wrote the *Book of Cryptographic Messages*. It contains the first use of permutations and combinations, to list all possible Arabic words with and without vowels.^{[4]}

The rule to determine the number of permutations of *n* objects was known in Indian culture around 1150. The *Lilavati* by the Indian mathematician Bhaskara II contains a passage that translates to:

The product of multiplication of the arithmetical series beginning and increasing by unity and continued to the number of places, will be the variations of number with specific figures.^{[5]}

In 1677, Fabian Stedman described factorials when explaining the number of permutations of bells in change ringing. Starting from two bells: "first, *two* must be admitted to be varied in two ways", which he illustrates by showing 1 2 and 2 1.^{[6]} He then explains that with three bells there are "three times two figures to be produced out of three" which again is illustrated. His explanation involves "cast away 3, and 1.2 will remain; cast away 2, and 1.3 will remain; cast away 1, and 2.3 will remain".^{[7]} He then moves on to four bells and repeats the casting away argument showing that there will be four different sets of three. Effectively, this is a recursive process. He continues with five bells using the "casting away" method and tabulates the resulting 120 combinations.^{[8]} At this point he gives up and remarks:

Now the nature of these methods is such, that the changes on one number comprehends the changes on all lesser numbers, ... insomuch that a compleat Peal of changes on one number seemeth to be formed by uniting of the compleat Peals on all lesser numbers into one entire body;^{[9]}

Stedman widens the consideration of permutations; he goes on to consider the number of permutations of the letters of the alphabet and of horses from a stable of 20.^{[10]}

A first case in which seemingly unrelated mathematical questions were studied with the help of permutations occurred around 1770, when Joseph Louis Lagrange, in the study of polynomial equations, observed that properties of the permutations of the roots of an equation are related to the possibilities to solve it. This line of work ultimately resulted, through the work of Évariste Galois, in Galois theory, which gives a complete description of what is possible and impossible with respect to solving polynomial equations (in one unknown) by radicals. In modern mathematics, there are many similar situations in which understanding a problem requires studying certain permutations related to it.

As a bijection from a set to itself, a permutation is a function that *performs* a rearrangement of a set, and is not a rearrangement itself. An older and more elementary viewpoint is that permutations are the rearrangements themselves. To distinguish between these two, the identifiers *active* and *passive* are sometimes prefixed to the term *permutation*, whereas in older terminology *substitutions* and *permutations* are used.^{[14]}

Since writing permutations elementwise, that is, as piecewise functions, is cumbersome, several notations have been invented to represent them more compactly. *Cycle notation* is a popular choice for many mathematicians due to its compactness and the fact that it makes a permutation's structure transparent. It is the notation used in this article unless otherwise specified, but other notations are still widely used, especially in application areas.

this means that *σ* satisfies *σ*(1) = 2, *σ*(2) = 5, *σ*(3) = 4, *σ*(4) = 3, and *σ*(5) = 1. The elements of *S* may appear in any order in the first row. This permutation could also be written as:

Under this assumption, one may omit the first row and write the permutation in *one-line notation* as

that is, as an ordered arrangement of the elements of *S*.^{[16]}^{[17]} Care must be taken to distinguish one-line notation from the cycle notation described below. In mathematics literature, a common usage is to omit parentheses for one-line notation, while using them for cycle notation. The one-line notation is also called the *word representation* of a permutation.^{[18]} The example above would then be 2 5 4 3 1 since the natural order 1 2 3 4 5 would be assumed for the first row. (It is typical to use commas to separate these entries only if some have two or more digits.) This form is more compact, and is common in elementary combinatorics and computer science. It is especially useful in applications where the elements of *S* or the permutations are to be compared as larger or smaller.

Cycle notation describes the effect of repeatedly applying the permutation on the elements of the set. It expresses the permutation as a product of cycles; since distinct cycles are disjoint, this is referred to as "decomposition into disjoint cycles".^{[b]}

Since for every new cycle the starting point can be chosen in different ways, there are in general many different cycle notations for the same permutation; for the example above one has:

A convenient feature of cycle notation is that one can find a permutation's inverse simply by reversing the order of the elements in the permutation's cycles. For example

In some combinatorial contexts it is useful to fix a certain order for the elements in the cycles and of the (disjoint) cycles themselves. Miklós Bóna calls the following ordering choices the *canonical cycle notation*:

For example, (312)(54)(8)(976) is a permutation in canonical cycle notation.^{[22]} The canonical cycle notation does not omit one-cycles.

Richard P. Stanley calls the same choice of representation the "standard representation" of a permutation.^{[23]} and Martin Aigner uses the term "standard form" for the same notion.^{[18]} Sergey Kitaev also uses the "standard form" terminology, but reverses both choices; that is, each cycle lists its least element first and the cycles are sorted in decreasing order of their least, that is, first elements.^{[24]}

Some authors prefer the leftmost factor acting first,^{[26]}^{[27]}^{[28]}
but to that end permutations must be written to the *right* of their argument, often as an exponent, where *σ* acting on *x* is written *x*^{σ}; then the product is defined by *x*^{σ·π} = (*x*^{σ})^{π}. However this gives a *different* rule for multiplying permutations; this article uses the definition where the rightmost permutation is applied first.

The concept of a permutation as an ordered arrangement admits several generalizations that are not permutations, but have been called permutations in the literature.

This usage of the term *permutation* is closely related to the term *combination*. A *k*-element combination of an *n*-set *S* is a *k* element subset of *S*, the elements of which are not ordered. By taking all the *k* element subsets of *S* and ordering each of them in all possible ways, we obtain all the *k*-permutations of *S*. The number of *k*-combinations of an *n*-set, *C*(*n*,*k*), is therefore related to the number of *k*-permutations of *n* by:

For example, the number of distinct anagrams of the word MISSISSIPPI is:^{[31]}

A ** k-permutation** of a multiset

*M*is a sequence of length

*k*of elements of

*M*in which each element appears

*a number of times less than or equal to*its multiplicity in

*M*(an element's

*repetition number*).

Permutations, when considered as arrangements, are sometimes referred to as *linearly ordered* arrangements. In these arrangements there is a first element, a second element, and so on. If, however, the objects are arranged in a circular manner this distinguished ordering no longer exists, that is, there is no "first element" in the arrangement, any element can be considered as the start of the arrangement. The arrangements of objects in a circular manner are called **circular permutations**.^{[32]}^{[f]} These can be formally defined as equivalence classes of ordinary permutations of the objects, for the equivalence relation generated by moving the final element of the linear arrangement to its front.

Two circular permutations are equivalent if one can be rotated into the other (that is, cycled without changing the relative positions of the elements). The following four circular permutations on four letters are considered to be the same.

The circular arrangements are to be read counter-clockwise, so the following two are not equivalent since no rotation can bring one to the other.

The number of circular permutations of a set *S* with *n* elements is (*n* – 1)!.

The number of *n*-permutations with *k* disjoint cycles is the signless Stirling number of the first kind, denoted by *c*(*n*, *k*).^{[33]}

Every permutation of a finite set can be expressed as the product of transpositions.^{[36]}
Although many such expressions for a given permutation may exist, either they all contain an even or an odd number of transpositions. Thus all permutations can be classified as even or odd depending on this number.

The Cayley table on the right shows these matrices for permutations of 3 elements.

There are a number of properties that are directly related to the total ordering of *S*.

An *ascent* of a permutation *σ* of *n* is any position *i* < *n* where the following value is bigger than the current one. That is, if *σ* = *σ*_{1}*σ*_{2}...*σ*_{n}, then *i* is an ascent if *σ*_{i} < *σ*_{i+1}.

For example, the permutation 3452167 has ascents (at positions) 1, 2, 5, and 6.

An *ascending run* of a permutation is a nonempty increasing contiguous subsequence of the permutation that cannot be extended at either end; it corresponds to a maximal sequence of successive ascents (the latter may be empty: between two successive descents there is still an ascending run of length 1). By contrast an *increasing subsequence* of a permutation is not necessarily contiguous: it is an increasing sequence of elements obtained from the permutation by omitting the values at some positions.
For example, the permutation 2453167 has the ascending runs 245, 3, and 167, while it has an increasing subsequence 2367.

If a permutation has *k* − 1 descents, then it must be the union of *k* ascending runs.^{[38]}

An excedance of a permutation *σ*_{1}*σ*_{2}...*σ*_{n} is an index *j* such that *σ*_{j} > *j*. If the inequality is not strict (that is, *σ*_{j} ≥ *j*), then *j* is called a *weak excedance*. The number of *n*-permutations with *k* excedances coincides with the number of *n*-permutations with *k* descents.^{[40]}

Sometimes an inversion is defined as the pair of values (*σ*_{i},*σ*_{j}) whose order is reversed; this makes no difference for the *number* of inversions, and this pair (reversed) is also an inversion in the above sense for the inverse permutation *σ*^{−1}. The number of inversions is an important measure for the degree to which the entries of a permutation are out of order; it is the same for *σ* and for *σ*^{−1}. To bring a permutation with *k* inversions into order (that is, transform it into the identity permutation), by successively applying (right-multiplication by) adjacent transpositions, is always possible and requires a sequence of *k* such operations. Moreover, any reasonable choice for the adjacent transpositions will work: it suffices to choose at each step a transposition of *i* and *i* + 1 where *i* is a descent of the permutation as modified so far (so that the transposition will remove this particular descent, although it might create other descents). This is so because applying such a transposition reduces the number of inversions by 1; as long as this number is not zero, the permutation is not the identity, so it has at least one descent. Bubble sort and insertion sort can be interpreted as particular instances of this procedure to put a sequence into order. Incidentally this procedure proves that any permutation *σ* can be written as a product of adjacent transpositions; for this one may simply reverse any sequence of such transpositions that transforms *σ* into the identity. In fact, by enumerating all sequences of adjacent transpositions that would transform *σ* into the identity, one obtains (after reversal) a *complete* list of all expressions of minimal length writing *σ* as a product of adjacent transpositions.

The number of permutations of *n* with *k* inversions is expressed by a Mahonian number,^{[43]} it is the coefficient of *X*^{k} in the expansion of the product

which is also known (with *q* substituted for *X*) as the q-factorial [*n*]_{q}! . The expansion of the product appears in Necklace (combinatorics).

One way to represent permutations of *n* things is by an integer *N* with 0 ≤ *N* < *n*!, provided convenient methods are given to convert between the number and the representation of a permutation as an ordered arrangement (sequence). This gives the most compact representation of arbitrary permutations, and in computing is particularly attractive when *n* is small enough that *N* can be held in a machine word; for 32-bit words this means *n* ≤ 12, and for 64-bit words this means *n* ≤ 20. The conversion can be done via the intermediate form of a sequence of numbers *d*_{n}, *d*_{n−1}, ..., *d*_{2}, *d*_{1}, where *d*_{i} is a non-negative integer less than *i* (one may omit *d*_{1}, as it is always 0, but its presence makes the subsequent conversion to a permutation easier to describe). The first step then is to simply express *N* in the *factorial number system*, which is just a particular mixed radix representation, where, for numbers less than *n*!, the bases (place values or multiplication factors) for successive digits are (*n* − 1)!, (*n* − 2)!, ..., 2!, 1!. The second step interprets this sequence as a Lehmer code or (almost equivalently) as an inversion table.

In the **Lehmer code** for a permutation *σ*, the number *d*_{n} represents the choice made for the first term *σ*_{1}, the number *d*_{n−1} represents the choice made for the second term
*σ*_{2} among the remaining *n* − 1 elements of the set, and so forth. More precisely, each *d*_{n+1−i} gives the number of *remaining* elements strictly less than the term *σ*_{i}. Since those remaining elements are bound to turn up as some later term *σ*_{j}, the digit *d*_{n+1−i} counts the *inversions* (*i*,*j*) involving *i* as smaller index (the number of values *j* for which *i* < *j* and *σ*_{i} > *σ*_{j}). The **inversion table** for *σ* is quite similar, but here *d*_{n+1−k} counts the number of inversions (*i*,*j*) where *k* = *σ*_{j} occurs as the smaller of the two values appearing in inverted order.^{[44]} Both encodings can be visualized by an *n* by *n* **Rothe diagram**^{[45]} (named after Heinrich August Rothe) in which dots at (*i*,*σ*_{i}) mark the entries of the permutation, and a cross at (*i*,*σ*_{j}) marks the inversion (*i*,*j*); by the definition of inversions a cross appears in any square that comes both before the dot (*j*,*σ*_{j}) in its column, and before the dot (*i*,*σ*_{i}) in its row. The Lehmer code lists the numbers of crosses in successive rows, while the inversion table lists the numbers of crosses in successive columns; it is just the Lehmer code for the inverse permutation, and vice versa.

To effectively convert a Lehmer code *d*_{n}, *d*_{n−1}, ..., *d*_{2}, *d*_{1} into a permutation of an ordered set *S*, one can start with a list of the elements of *S* in increasing order, and for *i* increasing from 1 to *n* set *σ*_{i} to the element in the list that is preceded by *d*_{n+1−i} other ones, and remove that element from the list. To convert an inversion table *d*_{n}, *d*_{n−1}, ..., *d*_{2}, *d*_{1} into the corresponding permutation, one can traverse the numbers from *d*_{1} to *d*_{n} while inserting the elements of *S* from largest to smallest into an initially empty sequence; at the step using the number *d* from the inversion table, the element from *S* inserted into the sequence at the point where it is preceded by *d* elements already present. Alternatively one could process the numbers from the inversion table and the elements of *S* both in the opposite order, starting with a row of *n* empty slots, and at each step place the element from *S* into the empty slot that is preceded by *d* other empty slots.

Converting successive natural numbers to the factorial number system produces those sequences in lexicographic order (as is the case with any mixed radix number system), and further converting them to permutations preserves the lexicographic ordering, provided the Lehmer code interpretation is used (using inversion tables, one gets a different ordering, where one starts by comparing permutations by the *place* of their entries 1 rather than by the value of their first entries). The sum of the numbers in the factorial number system representation gives the number of inversions of the permutation, and the parity of that sum gives the signature of the permutation. Moreover, the positions of the zeroes in the inversion table give the values of left-to-right maxima of the permutation (in the example 6, 8, 9) while the positions of the zeroes in the Lehmer code are the positions of the right-to-left minima (in the example positions the 4, 8, 9 of the values 1, 2, 5); this allows computing the distribution of such extrema among all permutations. A permutation with Lehmer code *d*_{n}, *d*_{n−1}, ..., *d*_{2}, *d*_{1} has an ascent *n* − *i* if and only if *d*_{i} ≥ *d*_{i+1}.

In computing it may be required to generate permutations of a given sequence of values. The methods best adapted to do this depend on whether one wants some randomly chosen permutations, or all permutations, and in the latter case if a specific ordering is required. Another question is whether possible equality among entries in the given sequence is to be taken into account; if so, one should only generate distinct multiset permutations of the sequence.

An obvious way to generate permutations of *n* is to generate values for the Lehmer code (possibly using the factorial number system representation of integers up to *n*!), and convert those into the corresponding permutations. However, the latter step, while straightforward, is hard to implement efficiently, because it requires *n* operations each of selection from a sequence and deletion from it, at an arbitrary position; of the obvious representations of the sequence as an array or a linked list, both require (for different reasons) about *n*^{2}/4 operations to perform the conversion. With *n* likely to be rather small (especially if generation of all permutations is needed) that is not too much of a problem, but it turns out that both for random and for systematic generation there are simple alternatives that do considerably better. For this reason it does not seem useful, although certainly possible, to employ a special data structure that would allow performing the conversion from Lehmer code to permutation in *O*(*n* log *n*) time.

For generating random permutations of a given sequence of *n* values, it makes no difference whether one applies a randomly selected permutation of *n* to the sequence, or chooses a random element from the set of distinct (multiset) permutations of the sequence. This is because, even though in case of repeated values there can be many distinct permutations of *n* that result in the same permuted sequence, the number of such permutations is the same for each possible result. Unlike for systematic generation, which becomes unfeasible for large *n* due to the growth of the number *n*!, there is no reason to assume that *n* will be small for random generation.

The basic idea to generate a random permutation is to generate at random one of the *n*! sequences of integers *d*_{1},*d*_{2},...,*d*_{n} satisfying 0 ≤ *d*_{i} < *i* (since *d*_{1} is always zero it may be omitted) and to convert it to a permutation through a bijective correspondence. For the latter correspondence one could interpret the (reverse) sequence as a Lehmer code, and this gives a generation method first published in 1938 by Ronald Fisher and Frank Yates.^{[46]}
While at the time computer implementation was not an issue, this method suffers from the difficulty sketched above to convert from Lehmer code to permutation efficiently. This can be remedied by using a different bijective correspondence: after using *d*_{i} to select an element among *i* remaining elements of the sequence (for decreasing values of *i*), rather than removing the element and compacting the sequence by shifting down further elements one place, one swaps the element with the final remaining element. Thus the elements remaining for selection form a consecutive range at each point in time, even though they may not occur in the same order as they did in the original sequence. The mapping from sequence of integers to permutations is somewhat complicated, but it can be seen to produce each permutation in exactly one way, by an immediate induction. When the selected element happens to be the final remaining element, the swap operation can be omitted. This does not occur sufficiently often to warrant testing for the condition, but the final element must be included among the candidates of the selection, to guarantee that all permutations can be generated.

The resulting algorithm for generating a random permutation of

can be described as follows in pseudocode:
*a*[0], *a*[1], ..., *a*[*n* − 1]

This can be combined with the initialization of the array

as follows
*a*[*i*] = *i*

If *d*_{i+1} = *i*, the first assignment will copy an uninitialized value, but the second will overwrite it with the correct value *i*.

However, Fisher-Yates is not the fastest algorithm for generating a permutation, because Fisher-Yates is essentially a sequential algorithm and "divide and conquer" procedures can achieve the same result in parallel.^{[47]}

There are many ways to systematically generate all permutations of a given sequence.^{[48]}
One classic, simple, and flexible algorithm is based upon finding the next permutation in lexicographic ordering, if it exists. It can handle repeated values, for which case it generates each distinct multiset permutation once. Even for ordinary permutations it is significantly more efficient than generating values for the Lehmer code in lexicographic order (possibly using the factorial number system) and converting those to permutations. It begins by sorting the sequence in (weakly) increasing order (which gives its lexicographically minimal permutation), and then repeats advancing to the next permutation as long as one is found. The method goes back to Narayana Pandita in 14th century India, and has been rediscovered frequently.^{[49]}

The following algorithm generates the next permutation lexicographically after a given permutation. It changes the given permutation in-place.

For example, given the sequence [1, 2, 3, 4] (which is in increasing order), and given that the index is zero-based, the steps are as follows:

Following this algorithm, the next lexicographic permutation will be [1, 3, 2, 4], and the 24th permutation will be [4, 3, 2, 1] at which point *a*[*k*] < *a*[*k* + 1] does not exist, indicating that this is the last permutation.

This method uses about 3 comparisons and 1.5 swaps per permutation, amortized over the whole sequence, not counting the initial sort.^{[50]}

An alternative to the above algorithm, the Steinhaus–Johnson–Trotter algorithm, generates an ordering on all the permutations of a given sequence with the property that any two consecutive permutations in its output differ by swapping two adjacent values. This ordering on the permutations was known to 17th-century English bell ringers, among whom it was known as "plain changes". One advantage of this method is that the small amount of change from one permutation to the next allows the method to be implemented in constant time per permutation. The same can also easily generate the subset of even permutations, again in constant time per permutation, by skipping every other output permutation.^{[49]}

An alternative to Steinhaus–Johnson–Trotter is Heap's algorithm,^{[51]} said by Robert Sedgewick in 1977 to be the fastest algorithm of generating permutations in applications.^{[48]}

The algorithm is recursive. The following table exhibits a step in the procedure. In the previous step, all alternate permutations of length 5 have been generated. Three copies of each of these have a "6" added to the right end, and then a different transposition involving this last entry and a previous entry in an even position is applied (including the identity; that is, no transposition).

Permutations are used in the interleaver component of the error detection and correction algorithms, such as turbo codes, for example 3GPP Long Term Evolution mobile telecommunication standard uses these ideas (see 3GPP technical specification 36.212^{[58]}).
Such applications raise the question of fast generation of permutations satisfying certain desirable properties. One of the methods is based on the permutation polynomials. Also as a base for optimal hashing in Unique Permutation Hashing.^{[59]}