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The problem of optimally assigning <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a1107701.png" /> individuals to <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a1107702.png" /> jobs. It can be formulated as a [[Linear programming|linear programming]] problem that is a special case of the [[Transport problem|transport problem]]:
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maximize <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a1107703.png" />
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The problem of optimally assigning  $  m $
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individuals to  $  m $
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jobs. It can be formulated as a [[Linear programming|linear programming]] problem that is a special case of the [[Transport problem|transport problem]]:
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maximize  $  \sum _ {i,j }  c _ {ij }  x _ {ij }  $
  
 
subject to
 
subject to
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a1107704.png" /></td> </tr></table>
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$$
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\sum _ { j } x _ {ij }  = a _ {i} ,  i = 1 \dots m
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$$
  
 
(origins or supply),
 
(origins or supply),
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a1107705.png" /></td> </tr></table>
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$$
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\sum _ { i } x _ {ij }  = b _ {j} ,  j = 1 \dots n
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$$
  
(destinations or demand), where <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a1107706.png" /> and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a1107707.png" />, which is called the balance condition. The assignment problem arises when <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a1107708.png" /> and all <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a1107709.png" /> and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a11077010.png" /> are <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a11077011.png" />.
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(destinations or demand), where $  x _ {ij }  \geq  0 $
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and  $  \sum a _ {i} = \sum b _ {j} $,  
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which is called the balance condition. The assignment problem arises when $  m = n $
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and all a _ {i} $
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and $  b _ {j} $
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are $  1 $.
  
If all <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a11077012.png" /> and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a11077013.png" /> in the transposed problem are integers, then there is an optimal solution for which all <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a11077014.png" /> are integers (Dantzig's theorem on integral solutions of the transport problem).
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If all a _ {i} $
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and $  b _ {j} $
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in the transposed problem are integers, then there is an optimal solution for which all $  x _ {ij }  $
 +
are integers (Dantzig's theorem on integral solutions of the transport problem).
  
In the assignment problem, for such a solution <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a11077015.png" /> is either zero or one; <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a11077016.png" /> means that person <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a11077017.png" /> is assigned to job <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a11077018.png" />; the weight <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a11077019.png" /> is the utility of person <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a11077020.png" /> assigned to job <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/a/a110/a110770/a11077021.png" />.
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In the assignment problem, for such a solution $  x _ {ij }  $
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is either zero or one; $  x _ {ij }  = 1 $
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means that person $  i $
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is assigned to job $  j $;  
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the weight $  c _ {ij }  $
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is the utility of person $  i $
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assigned to job $  j $.
  
 
The special structure of the transport problem and the assignment problem makes it possible to use algorithms that are more efficient than the [[Simplex method|simplex method]]. Some of these use the Hungarian method (see, e.g., [[#References|[a5]]], [[#References|[a1]]], Chapt. 7), which is based on the König–Egervary theorem (see [[König theorem|König theorem]]), the method of potentials (see [[#References|[a1]]], [[#References|[a2]]]), the out-of-kilter algorithm (see, e.g., [[#References|[a3]]]) or the transportation simplex method.
 
The special structure of the transport problem and the assignment problem makes it possible to use algorithms that are more efficient than the [[Simplex method|simplex method]]. Some of these use the Hungarian method (see, e.g., [[#References|[a5]]], [[#References|[a1]]], Chapt. 7), which is based on the König–Egervary theorem (see [[König theorem|König theorem]]), the method of potentials (see [[#References|[a1]]], [[#References|[a2]]]), the out-of-kilter algorithm (see, e.g., [[#References|[a3]]]) or the transportation simplex method.

Latest revision as of 18:48, 5 April 2020


The problem of optimally assigning $ m $ individuals to $ m $ jobs. It can be formulated as a linear programming problem that is a special case of the transport problem:

maximize $ \sum _ {i,j } c _ {ij } x _ {ij } $

subject to

$$ \sum _ { j } x _ {ij } = a _ {i} , i = 1 \dots m $$

(origins or supply),

$$ \sum _ { i } x _ {ij } = b _ {j} , j = 1 \dots n $$

(destinations or demand), where $ x _ {ij } \geq 0 $ and $ \sum a _ {i} = \sum b _ {j} $, which is called the balance condition. The assignment problem arises when $ m = n $ and all $ a _ {i} $ and $ b _ {j} $ are $ 1 $.

If all $ a _ {i} $ and $ b _ {j} $ in the transposed problem are integers, then there is an optimal solution for which all $ x _ {ij } $ are integers (Dantzig's theorem on integral solutions of the transport problem).

In the assignment problem, for such a solution $ x _ {ij } $ is either zero or one; $ x _ {ij } = 1 $ means that person $ i $ is assigned to job $ j $; the weight $ c _ {ij } $ is the utility of person $ i $ assigned to job $ j $.

The special structure of the transport problem and the assignment problem makes it possible to use algorithms that are more efficient than the simplex method. Some of these use the Hungarian method (see, e.g., [a5], [a1], Chapt. 7), which is based on the König–Egervary theorem (see König theorem), the method of potentials (see [a1], [a2]), the out-of-kilter algorithm (see, e.g., [a3]) or the transportation simplex method.

In turn, the transportation problem is a special case of the network optimization problem.

A totally different assignment problem is the pole assignment problem in control theory.

References

[a1] D.B. Yudin, E.G. Gol'shtein, "Linear programming" , Israel Program Sci. Transl. (1965) (In Russian)
[a2] R. Frisch, "La résolution des problèmes de programme linéaire par la méthode du potentiel logarithmique" Cahier Sém. Econom. , 4 (1956) pp. 20–23
[a3] K. Murtz, "Linear and combinatorial programming" , Wiley (1976)
[a4] M. Grötschel, L. Lovász, A. Schrijver, "Geometric algorithms and combinatorial optimization" , Springer (1987)
[a5] C.H. Papadimitriou, K. Steiglitz, "Combinatorial optimization" , Prentice-Hall (1982)
How to Cite This Entry:
Assignment problem. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Assignment_problem&oldid=45228
This article was adapted from an original article by M. Hazewinkel (originator), which appeared in Encyclopedia of Mathematics - ISBN 1402006098. See original article