JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Heuristics for Locating Two Types of Public Health-Care Facilities
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Heuristics for Locating Two Types of Public Health-Care Facilities
Kim, Dong-Guen; Kim, Yeong-Dae; Lee, Tae-Sik;
  PDF(new window)
 Abstract
This paper discusses the problem of determining locations for public health-care facilities and allocating patients to the public facilities with the objective of minimizing the total construction cost. The public health-care facilities have two types of facilities: public hospitals and health centers. The public hospital provides both hospital services and homecare services, while the health center provides only homecare service. We present an integer programming formulation for the problem, and develop two types of heuristics, based on priority rules and approximate mathematical formulation. Results of a series of computational experiments on a number of problem instances show that the algorithms give good solutions in a reasonable computation time.
 Keywords
Healthcare Service;Location;Allocation;Heuristics;
 Language
English
 Cited by
1.
Capacitated Location and Allocation Models of Long-Term Care Facilities,;;;;

Industrial Engineering and Management Systems, 2013. vol.12. 3, pp.190-197 crossref(new window)
1.
A Lagrangian heuristic algorithm for a public healthcare facility location problem, Annals of Operations Research, 2013, 206, 1, 221  crossref(new windwow)
 References
1.
Adenso-Diaz, B. and Rodriguez, F. (1997), A simple search heuristic for the MCLP: application to the location of ambulance bases in a rural region, Omega, 25, 181-187. crossref(new window)

2.
Barreto, S., Ferreira, C., Paixao, J., and Santos, B. S. (2007), Using clustering analysis in a capacitated locationrouting problem, European Journal of Operational Research, 179, 968-977. crossref(new window)

3.
Berman, O., Verter, V., and Kara, B. Y. (2007), Designing emergency response networks for hazardous materials transportation, Computers and Operation zs Research, 34(5), 1374-1388. crossref(new window)

4.
Choi, S. S. and Lee, Y. H. (2007) The multi-period demand changing location problem, Journal of the Korean Institute of Industrial Engineers, 33, 439-446.

5.
Costa, A. M., Pranca, P. M., and Filho, C. L. (2011), Twolevel network design with intermediate facilities: an application to electrical distribution systems, Omega, 39, 3-13. crossref(new window)

6.
Daskin, M. S. (2008), What you should know about location modeling, Naval Research Logistics, 55, 283-294. crossref(new window)

7.
Daskin, M. S. and Dean, L. K. (2004), Location of health care facilities. In Brandeau, M. L., Sainford, F., and Pierskalla, W. P. (eds), Operations Research and Health Care: A Handbook of Methods and Applications (Boston: Kluwer Academic), chapter 3, 43-76.

8.
Dominguez, E. and Munoz, J. (2008), A neural model for the p-median problem, Computers and Operations Research, 35, 404-416. crossref(new window)

9.
Fathali, J. and Kakhki, H. T. (2006), Solving the p-median problem with pos/neg weights by variable neighborhood search and some results for special cases, European Journal of Operation Research, 170, 440- 462. crossref(new window)

10.
Galvao, R. D., Espejo, L. G. A., and Boffey, B. (2002), Ahierarchical model for the location of perinatal facilities in the municipality of Rio de Janeiro, European Journal of Operation Research, 138, 495-517. crossref(new window)

11.
Garey, M. R. and Johnson, D. S. (1979), Computers and Intractability: A Guide to the Theory of NP-Completeness, Freeman, New York, NY.

12.
Hale, T. S. and Moberg, C. R. (2003), Location science research: a review, Annals of Operation Research, 123, 21-35. crossref(new window)

13.
Hong, S. H. and Lee, Y. H. (2004), The maximal covering location problem with cost restrictions, Journal of the Korean Institute of Industrial Engineers, 30, 93-106.

14.
yaraman, V., Gupta, R., and Pirkul, H. (2003), Selecting hierarchical facilities in a service-operations environment, European Journal of Operational Research, 147, 613-628. crossref(new window)

15.
Jia, H., Ordonez, F., and Dessouky, M. (2007), A modeling framework for facility location of medical services for large-scale emergencies, IIE Transactions, 39, 41-55. crossref(new window)

16.
Kim, D.-G. and Kim, Y.-D. (2009), A Lagrangian heuristic algorithm for a public healthcare facility location problem, Technical Report 2009-03, Department of Industrial Engineering, Korea Advanced Institute of Science and Technology (KAIST).

17.
Kim, D.-G. and Kim, Y.-D. (2010), A branch and bound algorithm for determining locations of long-term care facilities, European Journal of Operation Research, 206, 168-177. crossref(new window)

18.
Lorena, L. A. N. and Senne, E. L. F. (2004), A column generation approach to capacitated p-median problems, Computers and Operations Research, 31, 863-876. crossref(new window)

19.
Lu, Z. and Bostel, N. (2007), A facility location model for logistics systems including reverse flows: the case of remanufacturing activities, Computers and Operations Research, 34, 299-323. crossref(new window)

20.
Ndiaye, M. and Alfares, H. (2008), Modeling health care facility location for moving population groups, Computers and Operations Research, 35, 2154-2161. crossref(new window)

21.
Obreque, C., Donoso, M., Gutierrez, G., and Marianov, V. (2010), A branch and cut algorithm for the hierarchical network design problem, European Journal of Operational Research, 200, 28-35. crossref(new window)

22.
Pacheco, J. A., Casado, S., Alegre, J. F., and Alvarez, A. (2008), Heuristic solutions for locating health resources, IEEE Intelligent Systems, 23, 57-63. crossref(new window)

23.
Pacheco, J. A. and Casado, S. (2005), Solving two location models with few facilities by using a hybrid heuristic: a real health resources case, Computers and Operations Research, 32, 3075-3091. crossref(new window)

24.
Rahman, S. and Smith, D. K. (2000), Use of locationallocation models in health service development planning in developing nations, European Journal of Operational Research, 123, 437-452. crossref(new window)

25.
ReVelle, C. S. and Eiselt, H. A. (2005), Location analysis: a synthesis and survey, European Journal of Operational Research, 165, 1-19. crossref(new window)

26.
ReVelle, C., Scholssberg, M., and Williams, J. (2008), Solving the maximal covering location problem with heuristic concentration, Computers and Operations Research, 35, 427-435. crossref(new window)

27.
Schobel, A., Hamacher, H. W., Liebers, A., and Wagner, D. (2009), The continuous stop location problem in public transportation networks, Asia-Pacific Journal of Operational Research, 26, 13-30. crossref(new window)

28.
Smith, H. K., Harper, P. R., Potts, C. N., and Thyle, A. (2009), Planning sustainable community health schemes in rural areas of developing countries, European Journal of Operational Research, 193, 768-777. crossref(new window)

29.
Syam, S. S. and Cote, M. J. (2010), A location-allocation model for service providers with application to not-for-profit health care organizations, Omega, 38, 157-166. crossref(new window)

30.
Verter, V. and Lapierre, S. D. (2002), Location of preventive health care facilities, Annals of Operations Research, 110, 123-132. crossref(new window)

31.
Wang, X.-F., Sun, X.-M., and Fang, Y. (2008), Genetic algorithm solution for multi-period two-echelon integrated competitive/uncompetitive facility location problem, Asia-Pacific Journal of Operational Research, 25, 33-56. crossref(new window)

32.
Weng, K., Yang, C., and Ma, Y.-F. (2006), Two artificial intelligence heuristics in solving multiple allocation hub maximal covering problem, Lecture Notes in Computer Science, 4113, 737-744.

33.
Zhang, J. (2006), Approximating the two-level facility location problem via a quasi-greedy approach, Mathematical Programming, 108, 159-176. crossref(new window)