Artigo - Open Access.

Idioma principal

EFFICIENT DETERMINATION OF HELIPORTS IN THE CITY OF RIO DE JANEIRO FOR THE OLYMPIC GAMES AND WORLD CUP: A FUZZY LOGIC APPROACH

Bisso, Claudio S.; Samanez, Carlos P.;

Artigo:

The purpose of this study was to determine a method of evaluation for the use and adaptation of Helicopter Landing Zones (HLZs) and their requirements for registered public-use for the Olympic Games and the World Cup. The proposed method involves two stages. The first stage consists of clustering the data obtained through the Aerial and Maritime Group/Military Police of the State of Rio de Janeiro (GAM/PMERJ). The second stage uses the weighted ranking method. The weighted ranking method was applied to a selection of locations using fuzzy logic, linguistic variables and a direct evaluation of the alternatives. Based upon the selection of four clusters, eight HLZs were obtained for ranking. The proposed method may be used to integrate the air space that will be used by the defense and state assistance agencies with the locations of the sporting events to be held in 2014 and 2016.

Artigo:

O objetivo desse trabalho é determinar um método que permita avaliar as Zonas de Pouso de Helicóptero (ZPH) que justifiquem investimento para sua adaptação aos requisitos previstos para helipontos de uso público registrados visando os Jogos Olímpicos e a Copa do Mundo. A metodologia utilizou duas etapas, a primeira através da clusterização dos dados obtidos através do GAM/PMERJ e a segunda através da aplicação do método de ranqueamento ponderado. O Método de ranqueamento ponderado aplica-se para a seleção de locais através da utilização da lógica fuzzy, utilizando variáveis lingüísticas e uma direta avaliação das alternativas. Baseado na seleção de quatro clusters, foram obtidas oito ZPH’s para serem ranqueadas. A metodologia proposta por este trabalho permite uma integração entre a malha aérea utilizada pelos órgãos de defesa e assistência do Estado com as locações onde serão realizados os eventos esportivos de 2014 e 2016.

Palavras-chave: Fuzzy logic, Site selection, Transport, Public Policy, Lógica Fuzzy,

Palavras-chave:

DOI: 10.5151/marine-spolm2014-126246

Referências bibliográficas
  • [1] Agrawal, S., Raghavendra, N., Tiwari, M.K., Goyal, S.K. (2010). A hybrid Taguchi-immune approach to optimize an integrated supply chain design problem with multiple shipping. European Journal of Operation Research, 203: 95–106.
  • [2] Aikens, C.H. (1985). Facility location models for distribution planning. European Journal of Operational Research, 22: 263–279.
  • [3] Chen, Y. and Qu, L. (2006). Evaluating the selection of logistics centre location using fuzzy mcdm model based on entropy weight. Proceedings of the 6th World Congress on Intelligent Control and Automation. Dailan, China, June 21-2
  • [4] Chi, S.C. and Kuo, R.J. (2001). Examination of the influence of fuzzy analytic hierarchy process in the development of an intelligent location selection support system of convenience store. IFSA World Congress and 20th NAFIPS International Conference. Joint 9th, Vol. 3, pp. 1312-1316.
  • [5] Hamacher, H.W., Nickel, S. (1998). Classification of location models. Location Science, 6: 229–242.
  • [6] Lee, H.M. (1996). Group decision making using fuzzy sets theory for evaluating the rate of aggregative risk in software development. Fuzzy Sets and Systems, 80: 261-271.
  • [7] Lee, S.M., Green, G.I., Kim, C. (1981). A multiple criteria model for the location–allocation problem. Computers and Operations Research, 8: 1–8.
  • [8] Levine, A. (1984). A model for health projections using knowledgeable informants. World Health Statistics Quarterly, 37: 306-317.
  • [9] Luenberger, D.G. (1984). Introduction to Linear and Nonlinear Programming (2nd ed). Addison-Wesley.
  • [10] MacQueen, J. (1967). Some methods for classification and analysis of multivariate observations. In: Proceedings of the fifth Berkley Symposium on Mathematical Statistics and Probability. Berkley, CA. University of California Press.
  • [11] Narasimhan, R. (1979). A fuzzy subset characterization of a site-selection problem. Decision Sciences, 10: 618–628.
  • [12] Pill, J. (1971). The Delphi method: substance, context, a critique and an annotated bibliography. Socio-Economic Planning Sciences, 5: 57-71.
  • [13] Rio de Janeiro. Office of Public Safety. Military Police. GAM/PMERJ 2010-2016 Multi-year plan. [Rio de Janeiro]: Aerial and Maritime Group, [2009].
  • [14] Ross, G.T., Soland, R.M. (1980). A multicriteria approach to location of public facilities. European Journal of Operational Research 4: 307–321.
  • [15] Sun, H., Gao, Z., Wu, J. (2008). A bi-level programming model and solution algorithm for the location of logistics distribution centers. Applied Mathematical Modeling, 32: 610–616.
  • [16] Terano, T. (1992). Fuzzy Systems Theory and Its Application. San Diego: Academic Press.
  • [17] Tsou, K.W., Hung, Y.T. and Chang, Y.L. (2005). An accessibility-based integrated measure of relative spatial equity in urban public facilities. Cities, 22: 424-435.
  • [18] Wei, L., Zhen-gang, Z., and Xinpu, W. (2008). Application of multi-objects fuzzy comprehension evaluation in selecting location of coal-fired plant construction project. MMIT, Proceedings of the 2008 International Conference on Multimedia and Information Technology. Washington, USA, Dec 30-31.
  • [19] Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8: 338–353.
  • [20] Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning. Information Sciences, 8: 199-249.
Como citar:

Bisso, Claudio S.; Samanez, Carlos P.; "EFFICIENT DETERMINATION OF HELIPORTS IN THE CITY OF RIO DE JANEIRO FOR THE OLYMPIC GAMES AND WORLD CUP: A FUZZY LOGIC APPROACH", p. 225-237 . In: In Anais do XVII Simpósio de Pesquisa Operacional e Logística da Marinha - SPOLM 2014 [=Blucher Engineering Proceedings, n.1, v.1]. São Paulo: Blucher, 2014.
ISSN 2358-5498, DOI 10.5151/marine-spolm2014-126246

últimos 30 dias | último ano | desde a publicação


downloads


visualizações


indexações