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OPTIMIZATION MODEL FOR THE RELOCATION OF DISTRIBUTION SITES OF ECONOMIC SUPPORT IN AREAS OF HIGH MARGINALIZATION

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JANUARY-DECEMBER 2016   -  Volume: 4 -  Pages: [15 p.]

DOI:

https://doi.org/10.6036/MN8104

Authors:

INGRID LANDA CRUZ - DIANA SANCHEZ PARTIDA - ERIKA BAROJAS PAYAN - JOSE LUIS MARTINEZ FLORES

Disciplines:

  • Organization and management of enterprises (LOGISTICA )

Downloads:   70

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Received Date :   11 July 2016

Reviewing Date :   10 November 2016

Accepted Date :   15 November 2016


Key words:
Pobreza, Zonas marginadas, Modelo Matemático, P-mediana, Optimización, Poverty, Fortunate Areas, Mathematical Model, P-median, Optimization.
Article type:
ARTICULO DE INVESTIGACION / RESEARCH ARTICLE
Section:
RESEARCH ARTICLES

In a globalized world, there are geographic areas where an economic and social lag is created. These situations allow us to determine areas of opportunity and to develop research cases for improvement. Nowadays Mexico is looking to eliminate poverty, having created social programs to help the less fortunate areas of the country. The municipality "La Perla" has 46 localities and is one of the municipalities with the highest poverty rate in the state of Veracruz. A survey was taken from some of the inhabitants of the 46 localities, where it was found that the locality where it takes the greatest amount of time to walk to collect financial support granted to them by the government through the program PROSPERA is 180 minutes, while the locality where it takes the least amount of time to walk to collect financial support is 20 minutes because the government aid program is found in the locality.

The main objective of this research is to minimize the distances the inhabitants must travel to receive their financial support from the government aid program locations that correspond to them. It is important to note that the five current government aid program locations and the localities assigned to them respectively were not selected under any mathematical model. The P-median was the mathematical model used in this study to obtain an improvement and was programmed in Lingo.

In this research, three different scenarios were obtained and with which a comparison was performed with respect to current allocations. From the first scenario in which the model calls for the best location of the 5 government aid program locations for the 46 localities, we can observe savings of almost 50%.

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