Uncertainties Modeling and Simulation of an Emergency Process with Fuzzy Petri Nets

Patrick Lallement

doi:doi:10.11648/j.ijmfs.20170301.11

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Uncertainties Modeling and Simulation of an Emergency Process with Fuzzy Petri Nets

Patrick Lallement

Published in International Journal of Management and Fuzzy Systems (Volume 3, Issue 1)

Received: 4 May 2016 Accepted: 24 February 2017 Published: 11 March 2017

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Abstract

This paper describes a way to model and simulate an emergency procedure with uncertainties. These uncertainties (especially due to visibility conditions, stress of actors) may have a strong influence on operational decisions and lead to a bad efficiency of the emergency system, due to a wrong resources management. These variables are considered and processed as fuzzy numbers and they are used as input of a simulation model with fuzzy Petri nets to evaluate the reactivity and the efficiency of the procedure.

Published in	International Journal of Management and Fuzzy Systems (Volume 3, Issue 1)
DOI	10.11648/j.ijmfs.20170301.11
Page(s)	1-9
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Organizational Modelling, Uncertainties, Petri Nets, Fuzzy Simulation

References

[1]	J-L. Wybo and K. Madland-Kowalski, “Command centres and emergency management support”, Safety Science, vol. 30, pp. 131-138, 1998.
[2]	Z. Linz, “Organisationnal Performance under Critical Situation – Exploring the role of computer modelling in crisis case analysis”, Computationnal and Mathematical Organization Theory, vol. 6, n°3, pp. 277-310, 2000.
[3]	C. Dautun, “Contribution to the study of hugh crisis, knowledge and decision-aided for civil security”, PhD thesis, Sciences and environment engineering, Ecole des Mines de St-Etienne, France, 2007.
[4]	C. Dautin, J. Tixier, F. Fontaine and G. Dusserre, “Crisis management: improvement of knowledge and developpement of a decision aid process”, Loss Preventioon Bulletin, vol. 201, pp. 16-21, 2008.
[5]	B. Balcik, “Relief chain planning and management: modelling and analyzing humanitarian logistic problem”, Industrial engineering, Washighton University, 2000.
[6]	C. Rongier, D. Gourc, M. Lauras and F. Galasso, “Toward a performance measurement system to control disaster responses”, in Collaborative networks for a sustainable world, L. Camarinha-Matos and B. X. H Afsarmaneh, Eds. St-Etienne, France, 2010, pp. 189-196.
[7]	C. Rongier, “Response to a crisis by performance management: towards a decision-aided tool, application to humanitarian”, PhD Thesis, Industrial Engineering, INP Toulouse, France, 2012.
[8]	M. Christopher, “Logistics and Supply Chain”, Prentice-Hall, New York, 2005.
[9]	R. Laroche, “Les événements naturels dommageables en France et dans le monde” (in French), Technical report, Ministry of Ecology, energy and sustainaible development, 2008.
[10]	P. Lagadec, “La gestion de crises” (in French), Paris, Ediscience, 1991.
[11]	L. Sayegh, W. Anthony and P. Perrewe, “Managerial decision-making under crisis: the role of emotion in an intuitive decision process”, Human Resource Management Review, vol. 14, pp. 179-199, 2004.
[12]	K. Kowalski-Trakofler, C. Vaught and T. Sharf, “Judgement and decision-making under stress, an overview of emergency managers”, International Journal of Emergency Management, vol. 1, n° 3, pp. 278-298, 2003.
[13]	M. Seeger, “Chaos and crisis: proposition for a general theory of crisis communication”, Public Relation Review, vol. 28, pp. 329-337, 2003.
[14]	L. Weisaerth and O. Knudsen, “Technological disasters, crisis management and leadership stress”, Journal of Hazardous Materials, vol. 93, n°1, pp. 35-45, 2002.
[15]	R. Billings, T. Milburn and M. Schaalman, “A model of crisis perception: a theoretical and empirical analysis”, Administrative Science Quaterly, vol. 25, n°2, pp. 300-316, 1980.
[16]	C. Cassandras and S. Lafortune, “Introduction to discrete-event systems”, Springer US, New York, 2008.
[17]	I. Dzelme-Berzina, “Mathematical logic and quantum finite state automata”, Theoretical Computer Science, vol. 410, n°20, pp. 1952-1959, 2009.
[18]	M. Traore, E. Chatelet, E. Soulier and H. Gabbar, “Learning Diagnosis based on evolving fuzzy finite state automation”, Fort-Worth TX, 2014 Sept. 29-Oct. 2, pp. 41-50.
[19]	L. Zadeh, “Fuzzy sets”, Information and Control, vol. 8, pp. 338-353, 1965.
[20]	L. Zadeh, “Sets as a basis for a theory of possibility”, Fuzzy Sets and Systems, vol. 1, pp. 308-335, 1978.
[21]	D. Dubois and H. Prade, “Possibility Theory”, Plenum Press, New York, 1988.
[22]	D. Dubois and H. Prade, “The three semantics of fuzzy sets”, Fuzzy Sets and Systems, vol. 90, pp. 141-150, 1997.
[23]	L. Gomes and A. Steiger-Garçao, “Programmable controller design based on a synchronized-colored Petri net model and integrating fuzzy reasoning”, Lecture Notes in Computer Science, vol. 935, pp. 218-237, Springer-Verlag, Berlin, 1995.
[24]	J. Cardoso, R. Valette and D. Dubois, “Petri nets with uncertainty markings”, Lecture Notes in Computer Science, vol. 483, pp. 64-78, Springer-Verlag, Berlin, 1991.
[25]	S. Chanas and M. Nowakowski, “Single-value simulation of fuzzy variable”, Fuzzy Sets and Systems, vol. 25, pp. 43-57, 1988.
[26]	D. Dubois and H. Prade, “Random sets and fuzzy intervals analysis”, Fuzzy Sets and Systems, vol. 42, pp. 87-101, 1991.
[27]	D. Gien and S. Jacqmart, Design and Simulation of manufacturing systems facing imperfectly defined information, Simulation Modeling Practice and Theory, vol. 13, n°6, pp. 465-485, 2005.
[28]	P. Lallement, Simulation of IP networks, some guidelines based on A. I. and the fuzzy subseets theory, SICPRO, 2005, Jan. 25-28, Moscow, pp. 1016-1025.
[29]	D. Dubois, H. T. Nguyen and H. Prade, “Possibility Theory, Probability and Fuzzy Sets”, in Fundamentals of Fuzzy Sets, D. Dubois and H. Prade, Eds, Kluwer, Boston, 2000.

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APA Style

Patrick Lallement. (2017). Uncertainties Modeling and Simulation of an Emergency Process with Fuzzy Petri Nets. International Journal of Management and Fuzzy Systems, 3(1), 1-9. https://doi.org/10.11648/j.ijmfs.20170301.11

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ACS Style

Patrick Lallement. Uncertainties Modeling and Simulation of an Emergency Process with Fuzzy Petri Nets. Int. J. Manag. Fuzzy Syst. 2017, 3(1), 1-9. doi: 10.11648/j.ijmfs.20170301.11

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AMA Style

Patrick Lallement. Uncertainties Modeling and Simulation of an Emergency Process with Fuzzy Petri Nets. Int J Manag Fuzzy Syst. 2017;3(1):1-9. doi: 10.11648/j.ijmfs.20170301.11

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@article{10.11648/j.ijmfs.20170301.11,
  author = {Patrick Lallement},
  title = {Uncertainties Modeling and Simulation of an Emergency Process with Fuzzy Petri Nets},
  journal = {International Journal of Management and Fuzzy Systems},
  volume = {3},
  number = {1},
  pages = {1-9},
  doi = {10.11648/j.ijmfs.20170301.11},
  url = {https://doi.org/10.11648/j.ijmfs.20170301.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmfs.20170301.11},
  abstract = {This paper describes a way to model and simulate an emergency procedure with uncertainties. These uncertainties (especially due to visibility conditions, stress of actors) may have a strong influence on operational decisions and lead to a bad efficiency of the emergency system, due to a wrong resources management. These variables are considered and processed as fuzzy numbers and they are used as input of a simulation model with fuzzy Petri nets to evaluate the reactivity and the efficiency of the procedure.},
 year = {2017}
}

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TY  - JOUR
T1  - Uncertainties Modeling and Simulation of an Emergency Process with Fuzzy Petri Nets
AU  - Patrick Lallement
Y1  - 2017/03/11
PY  - 2017
N1  - https://doi.org/10.11648/j.ijmfs.20170301.11
DO  - 10.11648/j.ijmfs.20170301.11
T2  - International Journal of Management and Fuzzy Systems
JF  - International Journal of Management and Fuzzy Systems
JO  - International Journal of Management and Fuzzy Systems
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PB  - Science Publishing Group
SN  - 2575-4947
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AB  - This paper describes a way to model and simulate an emergency procedure with uncertainties. These uncertainties (especially due to visibility conditions, stress of actors) may have a strong influence on operational decisions and lead to a bad efficiency of the emergency system, due to a wrong resources management. These variables are considered and processed as fuzzy numbers and they are used as input of a simulation model with fuzzy Petri nets to evaluate the reactivity and the efficiency of the procedure.
VL  - 3
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Author Information

Patrick Lallement

Charles Delaunay Institute, UMR CNRS n° 6281, University of Technology of Troyes, Troyes, France

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APA Style

Patrick Lallement. (2017). Uncertainties Modeling and Simulation of an Emergency Process with Fuzzy Petri Nets. International Journal of Management and Fuzzy Systems, 3(1), 1-9. https://doi.org/10.11648/j.ijmfs.20170301.11

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ACS Style

Patrick Lallement. Uncertainties Modeling and Simulation of an Emergency Process with Fuzzy Petri Nets. Int. J. Manag. Fuzzy Syst. 2017, 3(1), 1-9. doi: 10.11648/j.ijmfs.20170301.11

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AMA Style

Patrick Lallement. Uncertainties Modeling and Simulation of an Emergency Process with Fuzzy Petri Nets. Int J Manag Fuzzy Syst. 2017;3(1):1-9. doi: 10.11648/j.ijmfs.20170301.11

Copy | Download

@article{10.11648/j.ijmfs.20170301.11,
  author = {Patrick Lallement},
  title = {Uncertainties Modeling and Simulation of an Emergency Process with Fuzzy Petri Nets},
  journal = {International Journal of Management and Fuzzy Systems},
  volume = {3},
  number = {1},
  pages = {1-9},
  doi = {10.11648/j.ijmfs.20170301.11},
  url = {https://doi.org/10.11648/j.ijmfs.20170301.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmfs.20170301.11},
  abstract = {This paper describes a way to model and simulate an emergency procedure with uncertainties. These uncertainties (especially due to visibility conditions, stress of actors) may have a strong influence on operational decisions and lead to a bad efficiency of the emergency system, due to a wrong resources management. These variables are considered and processed as fuzzy numbers and they are used as input of a simulation model with fuzzy Petri nets to evaluate the reactivity and the efficiency of the procedure.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Uncertainties Modeling and Simulation of an Emergency Process with Fuzzy Petri Nets
AU  - Patrick Lallement
Y1  - 2017/03/11
PY  - 2017
N1  - https://doi.org/10.11648/j.ijmfs.20170301.11
DO  - 10.11648/j.ijmfs.20170301.11
T2  - International Journal of Management and Fuzzy Systems
JF  - International Journal of Management and Fuzzy Systems
JO  - International Journal of Management and Fuzzy Systems
SP  - 1
EP  - 9
PB  - Science Publishing Group
SN  - 2575-4947
UR  - https://doi.org/10.11648/j.ijmfs.20170301.11
AB  - This paper describes a way to model and simulate an emergency procedure with uncertainties. These uncertainties (especially due to visibility conditions, stress of actors) may have a strong influence on operational decisions and lead to a bad efficiency of the emergency system, due to a wrong resources management. These variables are considered and processed as fuzzy numbers and they are used as input of a simulation model with fuzzy Petri nets to evaluate the reactivity and the efficiency of the procedure.
VL  - 3
IS  - 1
ER  -

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