Uma Abordagem de Integração de Simulação Baseada em Agentes e Mineração de Processos
Resumo
A simulação baseada em agentes de software é capaz de promover a especificação e verificação do comportamento de processos, tendo sido aplicada nas mais diversas áreas, como Biologia, Engenharias, Economia e Sociologia. Por outro lado, a mineração de processos proporciona a descoberta dos processos através de logs de eventos de sistemas automatizados. Neste trabalho, e proposto um estudo de integração destas duas diferentes abordagens, as quais apresentam um potencial interessante por serem complementares e permitirem a melhoria de processos no cenário organizacional. A princípio, as duas abordagens podem ser adequadamente integradas com foco no tratamento de eventos. Uma possibilidade de integração e modelar preliminarmente o processo e submete-lo a simulação com agentes, sendo que os eventos gerados poderão ser utilizados para redefinir o modelo de processo utilizando diversas técnicas de mineração. Através de modelos de integração das duas abordagens será possível verificar a existência de convergência no processo de definição e redescoberta de processos de negócio das organizações
Palavras-chave:
Simulação, Agentes, Mineração
Referências
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Georgakopoulos, D., Hornick, M. F., and Sheth, A. P. (1995). An overview of workflow management: From process modeling to workflow automation infrastructure. Distri- buted and Parallel Databases, 3(2):119–153.
Gunther, C. W. and van der Aalst, W. M. P. (2007). Fuzzy mining - adaptive process simplification based on multi-perspective metrics. In Alonso, G., Dadam, P., and Rosemann, M., editors, BPM, volume 4714 of Lecture Notes in Computer Science, pages 328–343. Springer.
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Medeiros, A. A., Weijters, A., and van der Aalst, W. (2007). Genetic process mining: An experimental evaluation. Journal of Data Mining and Knowledge Discovery, 14(2):245–304.
OMG (2008). Business Process Model and Notation. Object Management Group, v1.1 edition.
Pascalau, E., Giurca, A., and Wagner, G. (2009). Validating auction business processes using agent-based simulations. In Abramowicz, W., Maciaszek, L. A., Kowalczyk, R., and Speck, A., editors, BPSC, volume 147 of LNI, pages 95–109. GI.
Song, M., Gunther, C. W., and van der Aalst, W. M. P. (2008). Trace clustering in process mining. In Ardagna, D., Mecella, M., and Yang, J., editors, Business Process Mana-gement Workshops, volume 17 of Lecture Notes in Business Information Processing, pages 109–120. Springer.
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Wagner, G. and Diaconescu, I. M. (2009). Aor-simulation.org: cognitive agent simulation. In Sierra, C., Castelfranchi, C., Decker, K. S., and Sichman, J. S., editors, AAMAS (2), pages 1405–1406. IFAAMAS.
Walicki, M. and Ferreira, D. R. (2010). Mining sequences for patterns with non-repeating symbols. In IEEE Congress on Evolutionary Computation, pages 1–8. IEEE.
Weijters, A., van der Aalst, W., and de Medeiros, A. A. (2006). Process mining with the heuristicsminer algorithm. BETA Working Paper Series WP 166, Eindhoven University of Technology.
Wooldridge, M. (2009). An Introduction to Multiagent Systems. Wiley, Chichester, UK, 2. edition.
CMMI Product Team, Software Engineering Institute (2006). CMMI for Development v1.2. Carnegie Mellon University.
Davenport, T. H. (1993). Process Innovation – Reengineering Work through Information Technology. Harvard Business School Press.
Diaconescu, I. M. and Wagner, G. (2009). Agent-based simulations with beliefs and sparql-based ask-reply communication. In di Tosto, G. and Parunak, H. V. D., editors, MABS, volume 5683 of Lecture Notes in Computer Science, pages 86–97. Springer.
Eckert, M. and Bry, F. (2009). Complex event processing (cep). Informatik-Spektrum, 32(2):163–167.
Eriksson, H. E. and Penker, M. (2000). Business Modeling With UML: Business Patterns at Work. Wiley, 1 edition.
Ferreira, D. R. and Gillblad, D. (2009). Discovering process models from unlabelled event logs. In Dayal, U., Eder, J., Koehler, J., and Reijers, H. A., editors, Business Process Management, 7th International Conference, BPM 2009, Ulm, Germany, September 2009. Proceedings, volume 5701 of Lecture Notes in Computer Science, pages 143–158. Springer.
Ferreira, D. R., Zacarias, M., Malheiros, M., and Ferreira, P. (2007). Approaching process mining with sequence clustering: Experiments and findings. In Alonso, G., Dadam, P., and Rosemann, M., editors, BPM, volume 4714 of Lecture Notes in Computer Science, pages 360–374. Springer.
Georgakopoulos, D., Hornick, M. F., and Sheth, A. P. (1995). An overview of workflow management: From process modeling to workflow automation infrastructure. Distri- buted and Parallel Databases, 3(2):119–153.
Gunther, C. W. and van der Aalst, W. M. P. (2007). Fuzzy mining - adaptive process simplification based on multi-perspective metrics. In Alonso, G., Dadam, P., and Rosemann, M., editors, BPM, volume 4714 of Lecture Notes in Computer Science, pages 328–343. Springer.
Hammer, M. and Champy, J. (2003). Reengineering the corporation. HarperBusiness Essential. HarperBusiness, New York, NY, rev. and updated with a new authors’ note edition.
Laguna, M. and Marklund, J. (2004). Business process modeling, simulation and design. Pearson-Prentice hall, Upper Saddle River, New Jersey.
Medeiros, A. A., Weijters, A., and van der Aalst, W. (2007). Genetic process mining: An experimental evaluation. Journal of Data Mining and Knowledge Discovery, 14(2):245–304.
OMG (2008). Business Process Model and Notation. Object Management Group, v1.1 edition.
Pascalau, E., Giurca, A., and Wagner, G. (2009). Validating auction business processes using agent-based simulations. In Abramowicz, W., Maciaszek, L. A., Kowalczyk, R., and Speck, A., editors, BPSC, volume 147 of LNI, pages 95–109. GI.
Song, M., Gunther, C. W., and van der Aalst, W. M. P. (2008). Trace clustering in process mining. In Ardagna, D., Mecella, M., and Yang, J., editors, Business Process Mana-gement Workshops, volume 17 of Lecture Notes in Business Information Processing, pages 109–120. Springer.
van der Aalst, W., Hofstede, A. T., and Weske, M. (2003). Business process management: A survey. page 1019.
van der Aalst, W. M. P., Weijters, T., and Maruster, L. (2004). Workflow mining: Discovering process models from event logs. IEEE Trans. Knowl. Data Eng., 16(9):1128–1142.
van Dongen, B. F., Medeiros, A. K. A., Verbeek, H. M. W., Weijters, A. J. M. M., and van der Aalst, W. M. P. (2005). The prom framework: A new era in process mining tool support. In Ciardo, G. and Darondeau, P., editors, ICATPN, volume 3536 of Lecture Notes in Computer Science, pages 444–454. Springer.
Veiga, G. M. and Ferreira, D. R. (2009). Understanding spaghetti models with sequence clustering for prom. In Rinderle-Ma, S., Sadiq, S. W., and Leymann, F., editors, Busi- ness Process Management Workshops, volume 43 of Lecture Notes in Business Information Processing, pages 92–103. Springer.
Wagner, G. (2003). Aor modelling and simulation: Towards a general architecture for agent-based discrete event simulation. In Giorgini, P., Henderson-Sellers, B., and Winikoff, M., editors, AOIS, volume 3030 of Lecture Notes in Computer Science, pages 174–188. Springer.
Wagner, G. (2009). business rules and agent-based business process simulation. Simpósio Brasileiro de Sistemas de Informações (SBSI) - Brasília-DF.
Wagner, G. and Diaconescu, I. M. (2009). Aor-simulation.org: cognitive agent simulation. In Sierra, C., Castelfranchi, C., Decker, K. S., and Sichman, J. S., editors, AAMAS (2), pages 1405–1406. IFAAMAS.
Walicki, M. and Ferreira, D. R. (2010). Mining sequences for patterns with non-repeating symbols. In IEEE Congress on Evolutionary Computation, pages 1–8. IEEE.
Weijters, A., van der Aalst, W., and de Medeiros, A. A. (2006). Process mining with the heuristicsminer algorithm. BETA Working Paper Series WP 166, Eindhoven University of Technology.
Wooldridge, M. (2009). An Introduction to Multiagent Systems. Wiley, Chichester, UK, 2. edition.
Publicado
23/05/2011
Como Citar
SZIMANSKI, Fernando; RALHA, Célia G.; JACOBI, Ricardo P..
Uma Abordagem de Integração de Simulação Baseada em Agentes e Mineração de Processos. In: SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 7. , 2011, Salvador.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2011
.
p. 238-249.
DOI: https://doi.org/10.5753/sbsi.2011.14580.
