Skip to main content

The p-Median Problem

  • Chapter
  • First Online:
Location Science

Abstract

The p-median problem is central to much of discrete location modeling and theory. While the p-median problem is \( \mathcal{N}\mathcal{P} \)-hard on a general graph, it can be solved in polynomial time on a tree. A linear time algorithm for the 1-median problem on a tree is described. We also present a classical formulation of the problem. Basic construction and improvement algorithms are outlined. Results from the literature using various metaheuristics including tabu search, heuristic concentration, genetic algorithms, and simulated annealing are summarized. A Lagrangian relaxation approach is presented and used for computational results on 40 classical test instances as well as a 500-node instance derived from the most populous counties in the contiguous United States. We conclude with a discussion of multi-objective extensions of the p-median problem.

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 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Al-khedhairi A (2008) Simulated annealing metaheuristic for solving P-median problem. Int J Contemporary Math Sci 3:1357–1365

    Google Scholar 

  • Alp O, Erkut E, Drezner Z (2003) An efficient genetic algorithm for the p-median problem. Ann Oper Res 122:21–42

    Article  Google Scholar 

  • Beasley JE (1990) OR-library: distributing test problems by electronic mail. J Oper Res Soc 41:1069–1072

    Article  Google Scholar 

  • Chiyoshi F, Galvão RD (2000) A statistical analysis of simulated annealing applied to the p-median problem. Ann Oper Res 96:61–74

    Article  Google Scholar 

  • Church RL (2008) BEAMR: an exact and approximate model for the p-median problem. Comput Oper Res 35:417–426

    Article  Google Scholar 

  • Church RL, ReVelle CS (1974) The maximal covering location problem. Pap Reg Sci Assoc 32:101–118

    Article  Google Scholar 

  • Cohon JL (1978) Multiobjective programming and planning. Academic, New York

    Google Scholar 

  • Daskin MS (2013) Network and discrete location: models, algorithms and applications, 2nd edn. Wiley, New York

    Book  Google Scholar 

  • Fisher ML (1981) The Lagrangian relaxation method for solving integer programming problems. Manag Sci 27:1–18

    Article  Google Scholar 

  • Fisher ML (1985) An applications oriented guide to Lagrangian relaxation. Interfaces 15:10–21

    Article  Google Scholar 

  • Glover F (1990) Tabu search: a tutorial. Interfaces 20:74–94

    Article  Google Scholar 

  • Glover F, Laguna M (1997) Tabu search. Kluwer Academic Publishers, Boston

    Book  Google Scholar 

  • Goldberg DE (1989) Genetic algorithms in search, optimization and machine learning. Addison-Wesley, Reading

    Google Scholar 

  • Goldman AJ (1971) Optimal center location in simple networks. Transp Sci 5:212–221

    Article  Google Scholar 

  • Hakimi SL (1964) Optimum location of switching centers and the absolute centers and medians of a graph. Oper Res 12:450–459

    Article  Google Scholar 

  • Hakimi SL (1965) Optimum distribution of switching centers in a communication network and some related graph theoretic problems. Oper Res 13:462–475

    Article  Google Scholar 

  • Hansen P, Mladenović N (1997) Variable neighborhood search for the P-median. Locat Sci 5:207–226

    Article  Google Scholar 

  • Hansen P, Mladenović N (2001) Variable neighborhood search: principles and applications for the p-median. Eur J Oper Res 130:449–467

    Article  Google Scholar 

  • Haupt RL, Haupt SE (1998) Practical genetic algorithms. Wiley, New York

    Google Scholar 

  • Holland J (1975) Adaption in natural and artificial systems. The University of Michigan Press, Ann Arbor

    Google Scholar 

  • Kariv O, Hakimi SL (1979) An algorithmic approach to network location problems. II: the p-medians. SIAM J Appl Math 37:539–560

    Article  Google Scholar 

  • Kirkpatrick S (1984) Optimization by simulated annealing: quantitative studies. J Stat Phys 34:975–986

    Article  Google Scholar 

  • Maranzana FE (1964) On the location of supply points to minimize transport costs. Oper Res Q 15:261–270

    Article  Google Scholar 

  • Michalewicz Z (1994) Genetic algorithms + data structures = evolution programs, 2nd edn. Springer, Berlin

    Book  Google Scholar 

  • Mitchell M (1998) An introduction to genetic algorithms. MIT Press, Cambridge

    Google Scholar 

  • Mladenović N, Hansen P (1997) Variable neighborhood search. Comput Oper Res 24:1097–1100

    Article  Google Scholar 

  • Mladenović N, Brimberg J, Hansen P, Moreno-Perez JA (2007) The p-median problem: a survey of metaheuristic approaches. Eur J Oper Res 179:927–939

    Article  Google Scholar 

  • Murray AT, Church RL (1996) Applying simulated annealing to location-planning problems. J Heuristics 2:31–53

    Article  Google Scholar 

  • ReVelle CS, Eiselt HA, Daskin MS (2008) A bibliography of some fundamental problem categories in discrete location science. Eur J Oper Res 184:817–848

    Article  Google Scholar 

  • Rolland E, Schilling DA, Current JR (1996) An efficient tabu search procedure for the p-median problem. Eur J Oper Res 96:329–342

    Article  Google Scholar 

  • Rosing KE, ReVelle CS (1997) Heuristic concentration: two stage solution construction. Eur J Oper Res 97:75–86

    Article  Google Scholar 

  • Rosing KE, ReVelle CS, Rolland E, Schilling DA, Current JR (1998) Heuristic concentration and tabu search: a head-to-head comparison. Eur J Oper Res 104:93–99

    Article  Google Scholar 

  • Tamir A (1996) An O(pn 2) algorithm for the p-median and related problems on tree graphs. Oper Res Lett 19:59–64

    Article  Google Scholar 

  • Teitz MB, Bart P (1968) Heuristic methods for estimating generalized vertex median of a weighted graph. Oper Res 16:955–961

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mark S. Daskin .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Daskin, M.S., Maass, K.L. (2015). The p-Median Problem. In: Laporte, G., Nickel, S., Saldanha da Gama, F. (eds) Location Science. Springer, Cham. https://doi.org/10.1007/978-3-319-13111-5_2

Download citation

Publish with us

Policies and ethics