SimOrgMaturity-Tool: Simulador para Avaliação Fuzzy de Maturidade Organizacional
Resumo
Este trabalho tem como objetivo apresentar um simulador para medir a maturidade das empresas, em referência à gestão por processos de negócios com base no modelo PEMM (Process Enterprise Maturity Model). Em frente às dificuldades de se medir a maturidade das empresas um Índice de Transformação Organizacional (ITO) foi criado para auxiliar na avaliação das organizações. Além deste Índice, a lógica Fuzzy é utilizada para proporcionar flexibilidade na análise, devido aos pontos incertos da avaliação. Sim-OrgMaturity-Tool possibilita alterar diversas vezes o valor das maturidades de cada atributo a fim de analisar o comportamento do ITO ao longo das mudanças. Esse simulador pode ser utilizado também como uma ferramenta de ensino de gestão por processos de negócios, tendo sido testado por um especialista na área.
Palavras-chave:
Gerenciamento de Processos, Modelo de maturidade, Sistemas de Inferencia Fuzzy, Lógica Fuzzy
Referências
M. K. I. Abdul Rahim, Y. Zhong, E.-H. Aghezzaf, and T. Aouam. Modelling and solving the multiperiod inventory-routing problem with stochastic stationary demand rates. International Journal of Production Research, 52(14):4351–4363, 2014.
D. Adelman. A price-directed approach to stochastic inventory/routing. Operations Research, 52(4):499–514, 2004.
P. P. Belfiore, O. L. d. V. Costa, and L. P. L. F´avero. Problema de estoque e roteiriza¸c˜ao: revis˜ao bibliogr´afica. Production, 16:442 – 454, 12 2006.
L. Bertazzi, A. Bosco, F. Guerriero, and D. Lagana. A stochastic inventory routing problem with stock-out. Transportation Research Part C: Emerging Technologies, 27:89–107, 2013.
G. R. Bitran and H. Yanasse. Computational complexity of the capacitated lot size problem. Management Science, 28(10):1271–81, 1982.
J. C´aceres-Cruz, A. A. Juan, T. Bektas, S. E. Grasman, and J. Faulin. Combining Monte Carlo simulation with heuristics for solving the inventory routing problem with stochastic demands. page 274, 2012.
G. Clarke and J. W. Wright. Scheduling of vehicles from a central depot to a number of delivery points. Operations research, 12(4):568–581, 1964.
L. C. Coelho, J.-F. Cordeau, and G. Laporte. Thirty years of inventory routing. Transportation Science, 48(1):1–19, 2013.
R. A. de Carvalho Oliveira, K. V. Delgado, and D. A. Moreira. Sistema para roteamento de ve´ıculos capacitados aplicando m´etodos de Monte Carlo. iSys-Revista Brasileira de Sistemas de Informa¸c˜ao, 8(3):42–63, 2016.
M. L. Fisher. The Lagrangian relaxation method for solving integer programming problems. Management science, 27(1):1–18, 1981.
H. M. Harmanani, D. Azar, N. Helal, and W. Keirouz. A simulated annealing algorithm for the capacitated vehicle routing problem. In Proceedings of the ISCA 26th International Conference on Computers and Their Applications, pages 96–101, 2011.
L. M. Hvattum, A. Løkketangen, and G. Laporte. Scenario tree-based heuristics for stochastic inventoryrouting problems. INFORMS Journal on Computing, 21(2):268–285, 2009.
A. A. Juan, S. E. Grasman, J. Caceres-Cruz, and T. Bekta¸s. A simheuristic algorithm for the singleperiod stochastic inventory-routing problem with stockouts. Simulation Modelling Practice and Theory, 46:40– 52, 2014.
S. Lin and B. W. Kernighan. An e↵ective heuristic algorithm for the traveling-salesman problem. Operations research, 21(2):498–516, 1973.
K. Shin and S. Han. A centroid-based heuristic algorithm for the capacitated vehicle routing problem. Computing and Informatics, 30(4):721–732, 2012.
N. Shukla, M. Tiwari, and D. Ceglarek. Geneticalgorithms-based algorithm portfolio for inventory routing problem with stochastic demand. International Journal of Production Research, 51(1):118–137, 2013.
Y. Yu, H. Chen, and F. Chu. A new model and hybrid approach for large scale inventory routing problems. European Journal of Operational Research, 189(3):1022–1040, 2008.
Y. Yu, F. Chu, and H. Chen. A model and algorithm for large scale stochastic inventory routing problem. In 2006 International Conference on Service Systems and Service Management, volume 1, pages 355–360. IEEE, 2006.
D. Adelman. A price-directed approach to stochastic inventory/routing. Operations Research, 52(4):499–514, 2004.
P. P. Belfiore, O. L. d. V. Costa, and L. P. L. F´avero. Problema de estoque e roteiriza¸c˜ao: revis˜ao bibliogr´afica. Production, 16:442 – 454, 12 2006.
L. Bertazzi, A. Bosco, F. Guerriero, and D. Lagana. A stochastic inventory routing problem with stock-out. Transportation Research Part C: Emerging Technologies, 27:89–107, 2013.
G. R. Bitran and H. Yanasse. Computational complexity of the capacitated lot size problem. Management Science, 28(10):1271–81, 1982.
J. C´aceres-Cruz, A. A. Juan, T. Bektas, S. E. Grasman, and J. Faulin. Combining Monte Carlo simulation with heuristics for solving the inventory routing problem with stochastic demands. page 274, 2012.
G. Clarke and J. W. Wright. Scheduling of vehicles from a central depot to a number of delivery points. Operations research, 12(4):568–581, 1964.
L. C. Coelho, J.-F. Cordeau, and G. Laporte. Thirty years of inventory routing. Transportation Science, 48(1):1–19, 2013.
R. A. de Carvalho Oliveira, K. V. Delgado, and D. A. Moreira. Sistema para roteamento de ve´ıculos capacitados aplicando m´etodos de Monte Carlo. iSys-Revista Brasileira de Sistemas de Informa¸c˜ao, 8(3):42–63, 2016.
M. L. Fisher. The Lagrangian relaxation method for solving integer programming problems. Management science, 27(1):1–18, 1981.
H. M. Harmanani, D. Azar, N. Helal, and W. Keirouz. A simulated annealing algorithm for the capacitated vehicle routing problem. In Proceedings of the ISCA 26th International Conference on Computers and Their Applications, pages 96–101, 2011.
L. M. Hvattum, A. Løkketangen, and G. Laporte. Scenario tree-based heuristics for stochastic inventoryrouting problems. INFORMS Journal on Computing, 21(2):268–285, 2009.
A. A. Juan, S. E. Grasman, J. Caceres-Cruz, and T. Bekta¸s. A simheuristic algorithm for the singleperiod stochastic inventory-routing problem with stockouts. Simulation Modelling Practice and Theory, 46:40– 52, 2014.
S. Lin and B. W. Kernighan. An e↵ective heuristic algorithm for the traveling-salesman problem. Operations research, 21(2):498–516, 1973.
K. Shin and S. Han. A centroid-based heuristic algorithm for the capacitated vehicle routing problem. Computing and Informatics, 30(4):721–732, 2012.
N. Shukla, M. Tiwari, and D. Ceglarek. Geneticalgorithms-based algorithm portfolio for inventory routing problem with stochastic demand. International Journal of Production Research, 51(1):118–137, 2013.
Y. Yu, H. Chen, and F. Chu. A new model and hybrid approach for large scale inventory routing problems. European Journal of Operational Research, 189(3):1022–1040, 2008.
Y. Yu, F. Chu, and H. Chen. A model and algorithm for large scale stochastic inventory routing problem. In 2006 International Conference on Service Systems and Service Management, volume 1, pages 355–360. IEEE, 2006.
Publicado
17/05/2017
Como Citar
CARVALHO,, Ivor; PENSO, Natália; FELIX, Tatiana; M.B.WERNECK, Vera.
SimOrgMaturity-Tool: Simulador para Avaliação Fuzzy de Maturidade Organizacional. In: SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 13. , 2017, Lavras.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2017
.
p. 585-592.
DOI: https://doi.org/10.5753/sbsi.2017.6091.
