Skip to main content

Assignment Problem

1955; Kuhn 1957; Munkres

  • Reference work entry
Encyclopedia of Algorithms
  • 341 Accesses

Keywords and Synonyms

Weighted bipartite matching    

Problem Definition

Assume that a complete bipartite graph, \( { G(X,Y,X \times Y) } \), with weights w(x, y) assigned to every edge (x, y) is given. A matching M is a subset of edges so that no two edges in M have a common vertex. A perfect matching is one in which all the nodes are matched. Assume that \( { |X|=|Y|=n } \). The weighted matching problem is to find a matching with the greatest total weight, where \( { w(M)=\sum_{e \in M} w(e) } \). Since G is a complete bipartite graph, it has a perfect matching. An algorithm that solves the weighted matching problem is due to Kuhn [4] and Munkres [6]. Assume that all edge weights are nonnegative.

Key Results

Define a feasible vertex labeling â„“ as a mapping from the set of vertices in G to the reals, where

$$ \ell(x) + \ell(y) \geq w(x,y) \:. $$

Call \( { \ell(x) } \) the label of vertex x. It is easy to compute a feasible vertex labeling as follows:

$$ \forall y \in Y\quad \ell(y) = 0 $$

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 399.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    This is the structure of explored edges when one starts BFS simultaneously from all free nodes in S. When one reaches a matched node in T, one only explores the matched edge; however, all edges incident to nodes in S are explored.

Recommended Reading

  1. Ahuja, R., Magnanti, T., Orlin, J.: Network Flows: Theory, Algorithms and Applications. Prentice Hall, Englewood Cliffs (1993)

    MATH  Google Scholar 

  2. Cook, W., Cunningham, W., Pulleyblank, W., Schrijver, A.: Combinatorial Optimization. Wiley, New York (1998)

    MATH  Google Scholar 

  3. Gabow, H.: Data structures for weighted matching and nearest common ancestors with linking. In: Symp. on Discrete Algorithms, 1990, pp. 434–443

    Google Scholar 

  4. Kuhn, H.: The Hungarian method for the assignment problem. Naval Res. Logist. Quart. 2, 83–97 (1955)

    Article  MathSciNet  Google Scholar 

  5. Lawler, E.: Combinatorial Optimization: Networks and Matroids. Holt, Rinehart and Winston (1976)

    Google Scholar 

  6. Munkres, J.: Algorithms for the assignment and transportation problems. J. Soc. Ind. Appl. Math. 5, 32–38 (1957)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag

About this entry

Cite this entry

Khuller, S. (2008). Assignment Problem. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30162-4_35

Download citation

Publish with us

Policies and ethics