A two-step approach to planning new facilities towards equal accessibility

Abstract

A recent advancement in location-allocation modeling proposes a new objective of minimizing inequality of accessibility. Existing work considers the planning problem as either selecting new sites or adjusting facility capacities, separately. This paper develops a two-step hybrid approach to the problem by optimizing both locations and capacities of facilities towards equal accessibility. A genetic algorithm is first employed to find the best locations to site new facilities, and then a quadratic programming method is used to determine the best capacity of each facility within a pre-defined range. The sequence is consistent with many decision-making practices. Results of a series of experiments demonstrate that location optimization reduces inequality in accessibility more significantly than capacity optimization. The two-step optimization method can be applied for sequential allocation decision-makings towards maximum equal accessibility.

Keywords

Location-allocation models equal accessibility two-step optimization

Get full access to this article

View all access options for this article.

References

Church

(1999) Location modelling and GIS. Geographical Information Systems 1: 293–303.

Church

ReVelle

(1974) The maximum covering location problem. Papers of the Regional Science Association 32: 101–118.

Culyer

Wagstaff

(1993) Equity and equality in health and health care. Journal of Health Economics 12: 431–457.

Fried

(1975) Rights and health care—beyond equity and efficiency. The New England Journal of Medicine 293: 241–245.

Garfinkel

Neebe

Rao

(1977) The m-center problem: Minimax facility location. Management Science 23: 1133–1142.

Wang

McGregor

(2010) Optimization of preventive health care facility locations. International Journal of Health Geographics 9: 17.

Krugman P (2013) Why inequality matters. New York Times, 15 December 2013.

Meyer

(2008) Equity and efficiency in regional policy. Periodica Mathematica Hungarica 56: 105–119.

Oliver

Mossialos

(2004) Equity of access to health care: Outlining the foundations for action. Journal of Epidemiology and Community Health 58: 655–658.

10.

Paez

Esita

Newbold

et al. (2013) Exploring resource allocation and alternate clinic accessibility landscapes for improved blood donor turnout. Applied Geography 45: 89–97.

11.

Polo

Acosta

Ferreira

et al. (2015) Location-allocation and accessibility models for improving the spatial planning of public health services. PLoS ONE 10(3): e0119190.

12.

Reese

(2006) Solution methods for the p-median problem. An annotated bibliography. Networks 48: 125–142.

13.

Tao

Cheng

Dai

et al. (2014) Spatial optimization of residential care facility locations in Beijing, China: Maximum equity in accessibility. International Journal of Health Geographics 13: 33.

14.

Teitz

Bart

(1968) Heuristic methods for estimating the generalized vertex median of a weighted graph. Operations Research 16: 955–961.

15.

Toregas

ReVelle

(1972) Optimal location under time or distance constraints. Papers in Regional Science 28: 133–144.

16.

Toussaint

(1983) Computing largest empty circles with location constraints. International Journal of Computer & Information Sciences 12: 347–358.

17.

Wang

(2012) Measurement, optimization, and impact of health care accessibility: A methodological review. Annals of the Association of American Geographers 102: 1104–1112.

18.

Wang

(2015) Quantitative Methods and Socio-Economic Applications in GIS, 2nd edn. Boca Raton, FL: CRC Press.

19.

Wang

Shi

(2015) Planning towards maximum equality in accessibility of NCI Cancer Centers in the U.S. In: Kanaroglou

Delmelle

Paez

(eds) Spatial Analysis in Health Geography, Farnham, UK: Ashgate, pp. 261–274.

20.

Wang

Tang

(2013) Planning toward equal accessibility to services: A quadratic programming approach. Environment and Planning B: Planning and Design 40: 195–212.