A New Multi Objective Approach for Optimizing p-median Modeling in School Allocation using Genetic Algorithm
Resumo
This paper proposes a new methodology for a multi parameter approach using the p-median. The optimized solution must fulfill the following criteria: It must minimize distances between cities without a university to a city that has a university; It must prioritize cities with a higher population; It must prioritize cities with a lower United Nation Human Development Index. The use of a multiparametric approach was only possible by introducing the concept of a generalized distance. The results compare the existing distribution of campuses of the Federal system with the best location resulting from the multi parameter method proposed here. Locations for expansion of the current established university in Amazonas State, Brazil, are proposed.
Referências
Abdoun, O., Abouchabaka, J., & Tajani, C. (2012). Analyzing the Performance of Mutation Operators to Solve the Travelling Salesman Problem. International Journal of Emerging Sciences, 2(1), 61-77.
Amaya, J., Peeters, D., Uribe, P., & Valenzuela, J. P. (2015). Optimization Modeling for Resource Allocation in the Chilean Public Education System. International Regional Science, 39(2), 155-176.
Brazilian Institute of Geography and Statistics – IBGE (2012). Union Official Journal, 1, 65 - 246. Secondary School Students Achievements.
Brazilian Institute of Geography and Statistics – IBGE (2010). XII Demographic Census.
Bussab, W. O., & Morettin, P. A. (2009). Basic Statistics. (6th ed.). Saraiva Publisher. (Section 3.1: Position Measures).
Chong, E. K. P & Zak, S. H. (2013). An Introduction to Optimization. (4th Ed.). Canada. John Wiley & Sons. (Chapter 14: Global Search Algorithms).
Federal University of Amazonas - UFAM (2006). Institutional Development Plan 2006-2015. [link]. Accessed: 08.08.16.
Gac, I., Martínez, F., & Weintraub, A. (2009). A deterministic linear optimization model for allocating schools to zones. Journal of the Operational Research Society, 60, 895-905.
Holland, J. H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press.
Kariv, O., & Hakimi, S. L. (1979). An algorithmic approach to network location problems. II: the p-medians. Journal of Applied Mathematics, 37, 539–560.
Menezes, R. F., & Pizzolato, N. D. (2014). Locating public schools in fast expanding areas: application of the capacitated p-median and maximal covering location models. Pesquisa Operacional, 34(2), 301-317.
Ministry of Education (2010). VIII National REUNI Workshop: Federal Universities - Consolidation and Expansion 2011-2020, Support for the National Education Plan. Brazil.
National Waterway Transportation Agency – ANTAQ (2013). Characterization of supply and demand in the inland waterways of the Amazon region passengers.
OECD report (2015). Education at a Glance 2015: OECD Indicators. OECD Publishing, Paris. DOI: 10.1787/eag-2015-en. Accessed in 29.08.16.
Picek, S., Jakobovic, D., & Golub, M. (2013). On the recombination operator in the real-coded genetic algorithms, IEEE Congress on Evolutionary Computation, pp. 3103-3110.
Pizzolato, N. D., Barcelos, F. B., & Lorena, L. A. (2004). School location methodology in urban areas of developing countries. International Transactions in Operational Research, 11(6), 667–681.
Teixeira, J., Antunes, A., & Peeters, D. (2007). An Optimization-Based Study on the Redeployment of a Secondary School Network. Environment and Planning B: Planning and Design, 34(2), 296-315.
Xavier, C. M., Costa, M. G. F., & Costa Filho, C. F. F. (2016). Optimizing Universities Allocation with Integer Programming Using a New Distance Measure. In: 5th International Conference on Engineeering Optimization (EngOpt), Iguassu Falls-Brazil. Proceedings of 5th EngOpt, 2016. v. 1. p. 1-10.
Xu, R., & Wunsch, D. C. (2008). Clustering. IEEE Press Series on Computational Intelligence (Section 2.2: Definition of Proximity Measures).
Amaya, J., Peeters, D., Uribe, P., & Valenzuela, J. P. (2015). Optimization Modeling for Resource Allocation in the Chilean Public Education System. International Regional Science, 39(2), 155-176.
Brazilian Institute of Geography and Statistics – IBGE (2012). Union Official Journal, 1, 65 - 246. Secondary School Students Achievements.
Brazilian Institute of Geography and Statistics – IBGE (2010). XII Demographic Census.
Bussab, W. O., & Morettin, P. A. (2009). Basic Statistics. (6th ed.). Saraiva Publisher. (Section 3.1: Position Measures).
Chong, E. K. P & Zak, S. H. (2013). An Introduction to Optimization. (4th Ed.). Canada. John Wiley & Sons. (Chapter 14: Global Search Algorithms).
Federal University of Amazonas - UFAM (2006). Institutional Development Plan 2006-2015. [link]. Accessed: 08.08.16.
Gac, I., Martínez, F., & Weintraub, A. (2009). A deterministic linear optimization model for allocating schools to zones. Journal of the Operational Research Society, 60, 895-905.
Holland, J. H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press.
Kariv, O., & Hakimi, S. L. (1979). An algorithmic approach to network location problems. II: the p-medians. Journal of Applied Mathematics, 37, 539–560.
Menezes, R. F., & Pizzolato, N. D. (2014). Locating public schools in fast expanding areas: application of the capacitated p-median and maximal covering location models. Pesquisa Operacional, 34(2), 301-317.
Ministry of Education (2010). VIII National REUNI Workshop: Federal Universities - Consolidation and Expansion 2011-2020, Support for the National Education Plan. Brazil.
National Waterway Transportation Agency – ANTAQ (2013). Characterization of supply and demand in the inland waterways of the Amazon region passengers.
OECD report (2015). Education at a Glance 2015: OECD Indicators. OECD Publishing, Paris. DOI: 10.1787/eag-2015-en. Accessed in 29.08.16.
Picek, S., Jakobovic, D., & Golub, M. (2013). On the recombination operator in the real-coded genetic algorithms, IEEE Congress on Evolutionary Computation, pp. 3103-3110.
Pizzolato, N. D., Barcelos, F. B., & Lorena, L. A. (2004). School location methodology in urban areas of developing countries. International Transactions in Operational Research, 11(6), 667–681.
Teixeira, J., Antunes, A., & Peeters, D. (2007). An Optimization-Based Study on the Redeployment of a Secondary School Network. Environment and Planning B: Planning and Design, 34(2), 296-315.
Xavier, C. M., Costa, M. G. F., & Costa Filho, C. F. F. (2016). Optimizing Universities Allocation with Integer Programming Using a New Distance Measure. In: 5th International Conference on Engineeering Optimization (EngOpt), Iguassu Falls-Brazil. Proceedings of 5th EngOpt, 2016. v. 1. p. 1-10.
Xu, R., & Wunsch, D. C. (2008). Clustering. IEEE Press Series on Computational Intelligence (Section 2.2: Definition of Proximity Measures).
Publicado
02/07/2017
Como Citar
XAVIER, Clahildek Matos; COSTA, Marly Guimarães Fernandes; COSTA FILHO, Cícero Ferreira Fernandes.
A New Multi Objective Approach for Optimizing p-median Modeling in School Allocation using Genetic Algorithm. In: SEMINÁRIO INTEGRADO DE SOFTWARE E HARDWARE (SEMISH), 44. , 2017, São Paulo.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2017
.
p. 2575-2586.
ISSN 2595-6205.
DOI: https://doi.org/10.5753/semish.2017.3365.
