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In combinatorial
mathematics Mathematics is a field of study that discovers and organizes methods, Mathematical theory, theories and theorems that are developed and Mathematical proof, proved for the needs of empirical sciences and mathematics itself. There are many ar ...
, a derangement is a
permutation In mathematics, a permutation of a set can mean one of two different things: * an arrangement of its members in a sequence or linear order, or * the act or process of changing the linear order of an ordered set. An example of the first mean ...
of the elements of a set in which 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 is known as the subfactorial of or the derangement number or de Montmort number (after Pierre Remond de Montmort). Notations for subfactorials in common use include , , , or  . For , the subfactorial equals the nearest integer to , where denotes the
factorial In mathematics, the factorial of a non-negative denoted is the Product (mathematics), 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 ...
of and is Euler's number. The problem of counting derangements was first considered by Pierre Raymond de Montmort in his '' Essay d'analyse sur les jeux de hazard'' 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 receives 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 ''h''1's 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 = \left( n - 1 \right) \bigl( + \bigr) 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 , 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 and \left\lfloor x \right\rfloor is the floor function. 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 & \text n = 0, \\ n \cdot \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 objects that fix the object. Any intersection of a collection of of these sets fixes a particular set of objects and therefore contains (n-i)! permutations. There are such collections, so the inclusion–exclusion principle 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 ~. On the other hand, n!=\sum_^ \binom\ !i since we can choose n - i elements to be in their own place and derange the other elements in just ways, by definition.


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

From !n = n! \sum_^n \frac and e^x = \sum_^\infty by substituting 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 a branch of mathematics and statistics concerning events and numerical descriptions of how likely they are to occur. The probability of an event is a number between 0 and 1; the larger the probability, the more likely an e ...
that a randomly selected permutation of a large number of objects is a derangement. The probability converges to this limit extremely quickly as increases, which is why is the nearest integer to The above semi-log 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 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. 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 such that, for every element of the function's codomain, there exists one element in the function's domain such that . In other words, for a f ...
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 (
up to Two Mathematical object, mathematical objects and are called "equal up to an equivalence relation " * if and are related by , that is, * if holds, that is, * if the equivalence classes of and with respect to are equal. This figure of speech ...
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, NP-complete problems are the hardest of the problems to which ''solutions'' can be verified ''quickly''. Somewhat more precisely, a problem is NP-complete when: # It is a decision problem, meaning that for any ...
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. :


Footnotes


References


External links

* * * {{cite web , last = Weisstein , first = E.W. , author-link = Eric W. Weisstein , title = Derangement , publisher = MathWorld / Wolfram Research , url = http://mathworld.wolfram.com/Derangement.html , via = mathworld.wolfram.com Permutations Fixed points (mathematics) Integer sequences es:Subfactorial