Derangement
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combinatorial Combinatorics is an area of mathematics primarily concerned with counting, both as a means and an end in obtaining results, and certain properties of finite structures. It is closely related to many other areas of mathematics and has many ap ...
mathematics Mathematics is an area of knowledge that includes the topics of numbers, formulas and related structures, shapes and the spaces in which they are contained, and quantities and their changes. These topics are represented in modern mathematics ...
, a derangement is a
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 pro ...
of the elements of a
set Set, The Set, SET or SETS may refer to: Science, technology, and mathematics Mathematics *Set (mathematics), a collection of elements *Category of sets, the category whose objects and morphisms are sets and total functions, respectively Electro ...
, such that no element appears in its original position. In other words, a derangement is a permutation that has no fixed points. The number of derangements of a set of size ''n'' is known as the subfactorial of ''n'' or the ''n-''th derangement number or ''n-''th de Montmort number. Notations for subfactorials in common use include !''n,'' ''Dn'', ''dn'', or ''n''¡. For ''n'' > 0, the subfactorial !''n'' equals the nearest integer to ''n''!/''e,'' where ''n''! denotes the
factorial In mathematics, the factorial of a non-negative denoted is the product of all positive integers less than or equal The factorial also equals the product of n with the next smaller factorial: \begin n! &= n \times (n-1) \times (n-2) \ ...
of ''n'' and ''e'' is
Euler's number The number , also known as Euler's number, is a mathematical constant approximately equal to 2.71828 that can be characterized in many ways. It is the base of the natural logarithms. It is the limit of as approaches infinity, an expressi ...
. The problem of counting derangements was first considered by Pierre Raymond de Montmort in 1708; he solved it in 1713, as did Nicholas Bernoulli at about the same time.


Example

Suppose that a professor gave a test to 4 students – A, B, C, and D – and wants to let them grade each other's tests. Of course, no student should grade their own test. How many ways could the professor hand the tests back to the students for grading, such that no student received their own test back? Out of 24 possible permutations (4!) for handing back the tests, : there are only 9 derangements (shown in blue italics above). In every other permutation of this 4-member set, at least one student gets their own test back (shown in bold red). Another version of the problem arises when we ask for the number of ways ''n'' letters, each addressed to a different person, can be placed in ''n'' pre-addressed envelopes so that no letter appears in the correctly addressed envelope.


Counting derangements

Counting derangements of a set amounts to the ''hat-check problem'', in which one considers the number of ways in which ''n'' hats (call them ''h''1 through ''hn'') can be returned to ''n'' people (''P''1 through ''Pn'') such that no hat makes it back to its owner. Each person may receive any of the ''n'' − 1 hats that is not their own. Call the hat which the person ''P''1 receives ''hi'' and consider ''hi''’s owner: ''Pi'' receives either ''P''1's hat, ''h''1, or some other. Accordingly, the problem splits into two possible cases: # ''Pi'' receives a hat other than ''h''1. This case is equivalent to solving the problem with ''n'' − 1 people and ''n'' − 1 hats because for each of the ''n'' − 1 people besides ''P''1 there is exactly one hat from among the remaining ''n'' − 1 hats that they may not receive (for any ''Pj'' besides ''Pi'', the unreceivable hat is ''hj'', while for ''Pi'' it is ''h''1). Another way to see this is to rename ''h''1 to ''h''i, where the derangement is more explicit: for any ''j'' from 2 to ''n'', ''P''j cannot receive ''h''j. # ''Pi'' receives ''h''1. In this case the problem reduces to ''n'' − 2 people and ''n'' − 2 hats, because ''P''1 received ''hi''s hat and ''P''i received ''h1s hat, effectively putting both out of further consideration. For each of the ''n'' − 1 hats that ''P''1 may receive, the number of ways that ''P''2, …, ''Pn'' may all receive hats is the sum of the counts for the two cases. This gives us the solution to the hat-check problem: stated algebraically, the number !''n'' of derangements of an ''n''-element set is :!n = (n - 1) ( + ) for n \geq 2, where !0 = 1 and !1 = 0. The number of derangements of small lengths is given in the table below. There are various other expressions for !''n'', equivalent to the formula given above. These include :!n = n! \sum_^n \frac for n \geq 0 and :!n = \left \frac \right= \left\lfloor\frac+\frac\right\rfloor for n \geq 1, where \left x\right/math> is the
nearest integer function Rounding means replacing a number with an approximate value that has a shorter, simpler, or more explicit representation. For example, replacing $ with $, the fraction 312/937 with 1/3, or the expression with . Rounding is often done to obt ...
and \left\lfloor x \right\rfloor is the
floor function In mathematics and computer science, the floor function is the function that takes as input a real number , and gives as output the greatest integer less than or equal to , denoted or . Similarly, the ceiling function maps to the least int ...
.Hassani, M. "Derangements and Applications." J. Integer Seq. 6, No. 03.1.2, 1–8, 2003 Other related formulas include !n = \left\lfloor \frac \right\rfloor,\quad\ n \ge 1, !n = \left\lfloor \left(e + e^\right)n!\right\rfloor - \lfloor en!\rfloor,\quad n \geq 2, and !n = n! - \sum_^n \cdot ,\quad\ n \ge 1. The following recurrence also holds: !n = \begin 1 & \textn = 0, \\ n \left( !(n-1) \right) + (-1)^n & \textn > 0. \end


Derivation by inclusion–exclusion principle

One may derive a non-recursive formula for the number of derangements of an ''n''-set, as well. For 1\leq k \leq n we define S_k to be the set of permutations of ''n'' objects that fix the k-th object. Any intersection of a collection of ''i'' of these sets fixes a particular set of ''i'' objects and therefore contains (n-i)! permutations. There are such collections, so the
inclusion–exclusion principle In combinatorics, a branch of mathematics, the inclusion–exclusion principle is a counting technique which generalizes the familiar method of obtaining the number of elements in the union of two finite sets; symbolically expressed as : , A \cu ...
yields \begin , S_1 \cup \dotsm \cup S_n, &= \sum_i \left, S_i\ - \sum_ \left, S_i \cap S_j\ + \sum_ \left, S_i \cap S_j \cap S_k\ + \cdots + (-1)^ \left, S_1 \cap \dotsm \cap S_n\\\ &= (n - 1)! - (n - 2)! + (n - 3)! - \cdots + (-1)^ 0!\\ &= \sum_^n (-1)^(n - i)!\\ &= n!\ \sum_^n , \end and since a derangement is a permutation that leaves none of the ''n'' objects fixed, this implies !n = n! - \left, S_1 \cup \dotsm \cup S_n\ = n! \sum_^n \frac.


Growth of number of derangements as ''n'' approaches ∞

From !n = n! \sum_^n \frac and e^x = \sum_^\infty by substituting \textstyle x = -1 one immediately obtains that \lim_ = \lim_\sum_^n \frac = e^ \approx 0.367879\ldots. This is the limit of the
probability Probability is the branch of mathematics concerning numerical descriptions of how likely an event is to occur, or how likely it is that a proposition is true. The probability of an event is a number between 0 and 1, where, roughly speaking, ...
that a randomly selected permutation of a large number of objects is a derangement. The probability converges to this limit extremely quickly as ''n'' increases, which is why !''n'' is the nearest integer to ''n''!/''e''. The above
semi-log In science and engineering, a semi-log plot/graph or semi-logarithmic plot/graph has one axis on a logarithmic scale, the other on a linear scale. It is useful for data with exponential relationships, where one variable covers a large range o ...
graph shows that the derangement graph lags the permutation graph by an almost constant value. More information about this calculation and the above limit may be found in the article on the statistics of random permutations.


Asymptotic expansion in terms of Bell numbers

An asymptotic expansion for the number of derangements in terms of
Bell numbers In combinatorial mathematics, the Bell numbers count the possible partitions of a set. These numbers have been studied by mathematicians since the 19th century, and their roots go back to medieval Japan. In an example of Stigler's law of eponymy ...
is as follows: !n = \frac + \sum_^m \left(-1\right)^\frac + O\left(\frac\right), where m is any fixed positive integer, and B_k denotes the k-th
Bell number In combinatorial mathematics, the Bell numbers count the possible partitions of a set. These numbers have been studied by mathematicians since the 19th century, and their roots go back to medieval Japan. In an example of Stigler's law of eponymy ...
. Moreover, the constant implied by the big O-term does not exceed B_.


Generalizations

The problème des rencontres asks how many permutations of a size-''n'' set have exactly ''k'' fixed points. Derangements are an example of the wider field of constrained permutations. For example, the '' ménage problem'' asks if ''n'' opposite-sex couples are seated man-woman-man-woman-... around a table, how many ways can they be seated so that nobody is seated next to his or her partner? More formally, given sets ''A'' and ''S'', and some sets ''U'' and ''V'' of
surjection In mathematics, a surjective function (also known as surjection, or onto function) is a function that every element can be mapped from element so that . In other words, every element of the function's codomain is the image of one element of ...
s ''A'' → ''S'', we often wish to know the number of pairs of functions (''f'', ''g'') such that ''f'' is in ''U'' and ''g'' is in ''V'', and for all ''a'' in ''A'', ''f''(''a'') ≠ ''g''(''a''); in other words, where for each ''f'' and ''g'', there exists a derangement φ of ''S'' such that ''f''(''a'') = φ(''g''(''a'')). Another generalization is the following problem: :''How many anagrams with no fixed letters of a given word are there?'' For instance, for a word made of only two different letters, say ''n'' letters A and ''m'' letters B, the answer is, of course, 1 or 0 according to whether ''n'' = ''m'' or not, for the only way to form an anagram without fixed letters is to exchange all the ''A'' with ''B'', which is possible if and only if ''n'' = ''m''. In the general case, for a word with ''n''1 letters ''X''1, ''n''2 letters ''X''2, ..., ''n''''r'' letters ''X''''r'', it turns out (after a proper use of the inclusion-exclusion formula) that the answer has the form \int_0^\infty P_ (x) P_(x) \cdots P_(x) e^\, dx, for a certain sequence of polynomials ''P''''n'', where ''P''''n'' has degree ''n''. But the above answer for the case ''r'' = 2 gives an orthogonality relation, whence the ''P''''n'''s are the
Laguerre polynomials In mathematics, the Laguerre polynomials, named after Edmond Laguerre (1834–1886), are solutions of Laguerre's equation: xy'' + (1 - x)y' + ny = 0 which is a second-order linear differential equation. This equation has nonsingular solutions on ...
(
up to Two mathematical objects ''a'' and ''b'' are called equal up to an equivalence relation ''R'' * if ''a'' and ''b'' are related by ''R'', that is, * if ''aRb'' holds, that is, * if the equivalence classes of ''a'' and ''b'' with respect to ''R'' ...
a sign that is easily decided). In particular, for the classical derangements, one has that !n = \frac = \int_0^\infty(x - 1)^n e^dx where \Gamma(s,x) is the
upper incomplete gamma function In mathematics, the upper and lower incomplete gamma functions are types of special functions which arise as solutions to various mathematical problems such as certain integrals. Their respective names stem from their integral definitions, whic ...
.


Computational complexity

It is
NP-complete In computational complexity theory, a problem is NP-complete when: # it is a problem for which the correctness of each solution can be verified quickly (namely, in polynomial time) and a brute-force search algorithm can find a solution by trying ...
to determine whether a given
permutation group In mathematics, a permutation group is a group ''G'' whose elements are permutations of a given set ''M'' and whose group operation is the composition of permutations in ''G'' (which are thought of as bijective functions from the set ''M'' to ...
(described by a given set of permutations that generate it) contains any derangements.. .


References


External links

* * * * {{cite web , author = Weisstein, Eric W , author-link = Eric W. Weisstein , title = Derangement , publisher = MathWorld–A Wolfram Web Resource , url = http://mathworld.wolfram.com/Derangement.html Permutations Fixed points (mathematics) Integer sequences es:Subfactorial fr:Problème des rencontres