D. Mark, M. Abkowitz, P. Lepofsky, and . Cheng, Selecting criteria for designating hazardous materials highway routes, Transportation Research Record, p.65, 1333.

J. Alkemper, F. Donald, and . Mango, Concurrent simulation to explain reinsurance market price dynamics, Risk Management, vol.6, pp.13-17, 2005.

E. Alp, Risk-Based Transportation Planning Practice: Overall Methodology And A Case Example, INFOR: Information Systems and Operational Research, vol.33, issue.1, p.65, 1995.
DOI : 10.1080/03155986.1995.11732263

N. Arunraj, S. Mandal, and J. Maiti, Modeling uncertainty in risk assessment: An integrated approach with fuzzy set theory and Monte Carlo simulation, Accident Analysis & Prevention, vol.55, issue.59, pp.242-255
DOI : 10.1016/j.aap.2013.03.007

E. Avanesov, Risk management in iso 9000 series standards, International Conference on Risk Assessment and Management, pp.25-40, 2009.

S. Azaiez, G. Habchi, M. Huget, M. Pralus, and J. Tounsi, Multiagent oriented modeling and simulation for manufacturing systems control, 2007 5th IEEE International Conference on Industrial Informatics, pp.1079-1084, 2007.
DOI : 10.1109/INDIN.2007.4384925

M. Benita and . Beamon, Supply chain design and analysis : : Models and methods, International journal of production economics, vol.55, issue.79, pp.281-294, 1998.

F. Gary and . Bennett, Guidelines for chemical transportation safety, security and risk management2nd ed. 2008center for chemical process safety, aiche, wiley & sonhoboken , nj978-0-471-78242-1194 pp, Journal of Hazardous Materials, vol.166, issue.33, pp.1568-1610, 2009.

C. Bersani, Hazardous materials transportation : a literature review and an annotated bibliography Advanced technologies and methodologies for risk management in the global transport of dangerous goods, pp.33-63, 2008.

E. Bonabeau, Agent-based modeling: Methods and techniques for simulating human systems, Proceedings of the National Academy of Sciences, vol.99, issue.Supplement 3, pp.7280-7287, 2002.
DOI : 10.1073/pnas.082080899

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC128598

S. Bonvicini, G. Leonelli, and . Spadoni, Risk analysis of hazardous materials transportation: evaluating uncertainty by means of fuzzy logic, Journal of Hazardous Materials, vol.62, issue.1, pp.59-74, 1998.
DOI : 10.1016/S0304-3894(98)00158-7

H. Books, Reducing risks protecting people : Hse?s decision-making process, p.41, 2001.

A. Borshchev and A. Filippov, From system dynamics and discrete event to practical agent based modeling : reasons, techniques, tools, Proceedings of the 22nd international conference of the system dynamics society, number 22, p.92, 2004.

A. Borshchev and A. Filippov, From system dynamics and discrete event to practical agent based modeling : reasons, techniques, tools, Proceedings of the 22nd international conference of the system dynamics society, p.79, 2004.

E. Mark, . Borsuk, A. Craig, . Stow, H. Kenneth et al., A bayesian network of eutrophication models for synthesis, prediction, and uncertainty analysis, Ecological Modelling, vol.173, issue.2, pp.219-239, 2004.

P. Bottelberghs, Risk analysis and safety policy developments in the Netherlands, Journal of Hazardous Materials, vol.71, issue.1-3, pp.59-84, 2000.
DOI : 10.1016/S0304-3894(99)00072-2

P. Phelim and . Boyle, Options : A monte carlo approach, Journal of financial economics, vol.4, issue.3, pp.323-338, 1977.

F. David, . Brown, E. William, and . Dunn, Application of a quantitative risk assessment method to emergency response planning, Computers & Operations Research, vol.34, issue.5, pp.1243-1265, 2007.

P. Nancy, . Button, M. Park, and . Reilly, Uncertainty in incident rates for trucks carrying dangerous goods, Accident Analysis & Prevention, vol.32, issue.6, pp.797-804, 2000.

M. Kathleen, . Carley, B. Douglas, E. Fridsma, A. Casman et al., Biowar : scalable agent-based model of bioattacks. Systems, Man and Cybernetics, Part A : Systems and Humans, IEEE Transactions on, vol.36, issue.2, pp.252-265, 2006.

P. Carotenuto, S. Giordani, and S. Ricciardelli, Finding minimum and equitable risk routes for hazmat shipments, Computers & Operations Research, vol.34, issue.5, pp.1304-1327, 2007.
DOI : 10.1016/j.cor.2005.06.003

G. Christos, S. Cassandras, and . Lafortune, Introduction to discrete event systems, p.83, 2009.

J. Castillo, Route optimization for hazardous materials transport. International Institute for geo-Information science and earth observation, p.59, 2004.

M. Cerrada, J. Cardillo, J. Aguilar, and R. Faneite, Agents-based design for fault management systems in industrial processes, Computers in Industry, vol.58, issue.4, pp.313-328, 2007.
DOI : 10.1016/j.compind.2006.07.008

J. Chakraborty, P. Marc, and . Armstrong, Using Geographic Plume Analysis to assess community vulnerability to hazardous accidents, Computers, Environment and Urban Systems, vol.19, issue.5-6, pp.341-356, 1995.
DOI : 10.1016/0198-9715(95)00018-6

A. Charania, D. Olds, and . Depasquale, Sub-orbital space tourism market : Predictions of the future marketplace using agent-based modeling, SpaceWorks Engineering, Inc, vol.4, p.93, 2006.

S. Chauhan and D. Bowles, Incorporating uncertainty in dam safety assessment, Proceedings of the Australian Committee on Large Dams Risk Workshop, p.60, 2003.

N. Collier, Repast : An extensible framework for agent simulation. The University of Chicago, Social Science Research, vol.36, p.132, 2003.

R. Sheila and . Conway, An agent-based model for analyzing control policies and the dynamic service-time performance of a capacity-constrained air traffic management facility, p.93, 2006.

F. Cristian, Understanding fault-tolerant distributed systems, Communications of the ACM, vol.34, issue.2, pp.56-78, 1991.
DOI : 10.1145/102792.102801

J. Valerie, J. Davidson, A. Ryks, and . Fazil, Fuzzy risk assessment tool for microbial hazards in food systems, Fuzzy Sets and Systems, vol.157, issue.9, pp.1201-1210, 2006.

. Bernardo-de-bernardinis, Gmes fast track emergency response core service. GMES strategic implementation plan, p.29, 2007.

E. Demael, Modélisation de ladispersion etmosphérique en milieu complexe et incertitudes associées, p.64, 2007.

M. Diergardt, Modeling complex scenarios in computer based information systems for risk analysis, p.93, 2006.

D. Mark-d-'inverno, M. Kinny, M. Luck, and . Wooldridge, A formal specification of dmars, Intelligent Agents IV Agent Theories, Architectures, and Languages, pp.155-176, 1997.

D. Alejandro, . Domínguez-garcía, G. John, . Kassakian, E. Joel et al., An integrated methodology for the dynamic performance and reliability evaluation of fault-tolerant systems, Reliability Engineering & System Safety, issue.11, pp.931628-1649, 2008.

A. Kelwyn, . Souza, K. Suresh, and . Khator, A survey of petri net applications in modeling controls for automated manufacturing systems, Computers in industry, vol.24, issue.1, pp.5-16, 1994.

D. Dubois and H. Prade, What are fuzzy rules and how to use them. Fuzzy sets and systems, pp.169-185, 1996.
DOI : 10.1016/0165-0114(96)00066-8

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

J. Didier and . Dubois, Fuzzy sets and systems : theory and applications, p.153, 1980.

M. Dumas and A. Hofstede, UML Activity Diagrams as a Workflow Specification Language, The Unified Modeling Language Modeling Languages Concepts and Tools, pp.76-90, 2001.
DOI : 10.1007/3-540-45441-1_7

L. Dymova, P. Sevastjanov, and A. Tikhonenko, An interval type-2 fuzzy extension of the topsis method using alpha cuts. Knowledge-Based Systems, pp.116-127, 2015.

P. Erard and P. Déguénon, Simulation par événements discrets. PPUR presses polytechniques, p.83, 1996.

E. Erkut and A. Ingolfsson, Catastrophe Avoidance Models for Hazardous Materials Route Planning, Transportation Science, vol.34, issue.2, pp.165-179, 2000.
DOI : 10.1287/trsc.

L. Donald and . Ermak, User's manual for slab : An atmospheric dispersion model for denser-than-air-releases, p.54, 1990.

B. Fabiano, . Curro, R. Palazzi, and . Pastorino, A framework for risk assessment and decision-making strategies in dangerous good transportation, Journal of Hazardous Materials, vol.93, issue.1, pp.1-15, 2002.
DOI : 10.1016/S0304-3894(02)00034-1

R. Fairman, D. Carl, P. Mead, and . Williams, Environmental risk assessment : approaches, experiences and information sources, p.40, 1998.

J. Ferber and J. Perrot, Les systèmes multi-agents : vers une intelligence collective. InterEditions, pp.91-180, 1995.

S. Ferson and R. Kuhn, Propagating Uncertainty in Ecological Risk Analysis Using Interval and Fuzzy Arithmetic, Computer Techniques in Environmental Studies IV. Computational Mechanics Publications, pp.387-401, 1992.
DOI : 10.1007/978-94-011-1874-3_27

K. Fischer, P. Jo¨rgjo¨rg, M. Muïler, and . Pischel, Cooperative transportation scheduling: An application domain for dai, Applied Artificial Intelligence, vol.10, issue.1, pp.1-34, 1996.
DOI : 10.1080/088395196118669

K. Fischer, P. Jörg, M. Müller, and . Pischel, Unifying control in a layered agent architecture, p.91, 2011.

J. Flaus and O. Granddamas, Towards a formalisation of mads, system failure analysis model, lambda-mu 13. ESREL, p.136, 2002.

J. Flaus, Risk Analysis : Socio-technical and Industrial Systems, p.28, 2013.
DOI : 10.1002/9781118790021

J. Flaus, Risk Analysis : Socio-technical and Industrial Systems, p.41, 2013.
DOI : 10.1002/9781118790021

A. Virginia, . Folcik, C. Gary, . An, G. Charles et al., Theoretical biology and medical modelling, Theoretical Biology and Medical Modelling, vol.4, pp.39-93, 2007.

W. Jay and . Forrester, Industrial dynamics : a major breakthrough for decision makers, Harvard business review, vol.36, issue.4, pp.37-66, 1958.

J. W. Forrester, M. Fouladgar, E. Yazdani-chamzini, and . Zavadskas, Industrial Dynamics, Journal of the Operational Research Society, vol.48, issue.10, pp.1037-10411, 1997.
DOI : 10.1057/palgrave.jors.2600946

M. Fowler, UML distilled : a brief guide to the standard object modeling language, p.79, 2004.

C. William, J. Frank, R. Thill, and . Batta, Spatial decision support system for hazardous material truck routing, Transportation Research Part C : Emerging Technologies, vol.8, issue.1, pp.337-359, 2000.

C. Henry, . Frey, S. Edward, and . Rubin, Evaluate uncertainties in advanced process technologies, Chemical engineering progress, vol.88, issue.5, pp.63-70, 1992.

L. Gasser, M. Pitmanblaye, A. Light, P. Joiner, R. Sheldon et al., Collaboration as a facilitator of planning and problem solving on a computer based task, Distributed artificial intelligence British Journal of Psychology, vol.9, pp.471-483, 1989.

T. Daniel and . Gillespie, Markov processes : an introduction for physical scientists, p.83, 1991.

S. Theodore and . Glickman, Acts of god and acts of man : recent trends in natural disasters and major industrial accidents, 1992.

G. Gordon, A general purpose systems simulation program, eastern joint computer conference : computers-key to total systems control, Proceedings of the, pp.87-104, 1961.

R. Gregory and S. Lichtenstein, A hint of risk : tradeoffs between quantitative and qualitative risk factors, Insurance Mathematics and Economics, vol.3, issue.17, pp.248-281, 1996.

D. Grether, K. Fürbas, and . Nagel, Agent-based Modelling and Simulation of Air Transport Technology, Procedia Computer Science, vol.19, pp.821-828, 2013.
DOI : 10.1016/j.procs.2013.06.109

F. Arthur, C. Griffin, and . Stanish, An agent-based model of prehistoric settlement patterns and political consolidation in the lake titicaca basin of peru and bolivia, Structure and Dynamics, vol.2, issue.2, p.93, 2007.

S. Haber, A modified Monte-Carlo quadrature, Mathematics of Computation, vol.20, issue.95, pp.361-368, 1966.
DOI : 10.1090/S0025-5718-1966-0210285-0

J. Hammersley and K. Morton, A new Monte Carlo technique: antithetic variates, Mathematical proceedings of the Cambridge philosophical society, pp.449-475, 1956.
DOI : 10.1098/rspa.1951.0233

M. John, D. Hammersley, and . Handscomb, Percolation processes, Monte Carlo Methods, pp.134-141, 1964.

R. Steven, . Hanna, A. Gary, R. Briggs, and . Jr, Handbook on atmospheric diffusion National Oceanic and Atmospheric Administration , Oak Ridge, TN (USA) Atmospheric Turbulence and Diffusion Lab, p.178, 1982.

W. Douglas, . Harwood, G. John, E. R. Viner, and . Russell, Procedure for developing truck accident and release rates for hazmat routing, Journal of Transportation Engineering, vol.119, issue.177, pp.189-199, 1993.

C. Jon and . Helton, Uncertainty and sensitivity analysis techniques for use in performance assessment for radioactive waste disposal, Reliability Engineering & System Safety, vol.42, issue.2, pp.327-367, 1993.

J. Ernest, H. Henley, and . Kumamoto, Probabilistic risk assessment and management for engineers and scientists, p.37, 1996.

A. Hobday, . Smith, C. Ic-stobutzki, R. Bulman, . Daley et al., Ecological risk assessment for the effects of fishing, Fisheries Research, vol.108, issue.2-3, pp.372-384, 2011.
DOI : 10.1016/j.fishres.2011.01.013

N. Peter, H. , and W. Kröger, Risk analyses of transportation on road and railway from a european perspective, Safety Science, vol.40, issue.1, pp.337-357, 2002.

I. Iec, Safety aspects-guidelines for their inclusion in standards 27 [81] Documentation INERIS. Methodes pour evaluation et la prevention des risques accidentels (dra-006), Tech. Rep, p.55, 1999.

R. Nicholas and . Jennings, On agent-based software engineering, Artificial intelligence, vol.117, issue.88, pp.277-296, 2000.

R. Nicholas, K. Jennings, M. Sycara, and . Wooldridge, A roadmap of agent research and development. Autonomous agents and multi-agent systems, pp.7-38, 1998.

B. Jerry, Discrete-event system simulation. Pearson Education India, p.82, 1984.

M. Kaegi, . Mock, R. Ziegler, and . Nibali, Information systems risk analysis by agent-based modelling of business processes, Proceedings of the Seventeenth European Safety and Reliability Conference (ESREL06), pp.2277-2284, 2006.

M. Kaegi, Risk analysis of information systems by agent-based modeling of business processes, p.78, 2009.

M. Kaegi, R. Mock, and W. Kröger, Analyzing maintenance strategies by agent-based simulations: A feasibility study, Reliability Engineering & System Safety, vol.94, issue.9, pp.1416-1421, 2009.
DOI : 10.1016/j.ress.2009.02.002

S. Kaplan and B. Garrick, On The Quantitative Definition of Risk, Risk Analysis, vol.165, issue.3, pp.11-27, 1981.
DOI : 10.1111/j.1539-6924.1981.tb01350.x

W. David-kelton, M. Averill, and . Law, Simulation modeling and analysis, p.82, 2000.

W. David-kelton, P. Randall, D. A. Sadowski, and . Sadowski, Simulation with ARENA, p.107, 2002.

E. Kentel, Probabilistic-fuzzy health risk modeling, Stochastic Environmental Research and Risk Assessment, vol.18, issue.5, pp.324-338, 2004.
DOI : 10.1007/s00477-004-0187-3

I. Faisal, S. Khan, and . Abbasi, Assessment of risks posed by chemical industries?application of a new computer automated tool maxcred-iii, Journal of Loss Prevention in the Process Industries, pp.455-469, 1999.

I. Faisal, S. Khan, and . Abbasi, Major accidents in process industries and an analysis of causes and consequences, Journal of Loss Prevention in the process Industries, vol.12, issue.45, pp.361-378, 1999.

I. Faisal, S. Khan, and . Abbasi, A criterion for developing credible accident scenarios for risk assessment, Journal of Loss Prevention in the Process Industries, pp.467-475, 2002.

V. Vivek, . Khanzode, P. Maiti, and . Ray, Occupational injury and accident research : A comprehensive review, Safety Science, vol.50, issue.5, pp.1355-1367, 2012.

A. Kleyner and V. Volovoi, Application of Petri nets to reliability prediction of occupant safety systems with partial detection and repair, Reliability Engineering & System Safety, vol.95, issue.6, pp.606-613, 2010.
DOI : 10.1016/j.ress.2010.01.008

H. Frank and . Knight, Risk, uncertainty and profit. Courier Corporation, p.58, 2012.

L. Kuipers and . Niederreiter, Uniform distribution of sequences, interscience tracts, p.68, 1974.

A. Kumar and I. Xagoraraki, Human health risk assessment of pharmaceuticals in water : An uncertainty analysis for meprobamate, carbamazepine, and phenytoin. Regulatory toxicology and pharmacology, pp.146-156, 2010.

G. Kumar and J. Maiti, Modeling risk based maintenance using fuzzy analytic network process, Expert Systems with Applications, vol.39, issue.11, pp.9946-9954, 2012.
DOI : 10.1016/j.eswa.2012.01.004

M. Haitam-laarabi and E. Le-climat, Multi-criteria route optimization for dangerous goods transport using fuzzy risk assessment and agent-based traffic simulation, Circulaire du 10 mai 2010 récapitulant les règles méthodologiques applicables aux études de dangers, à l?appréciation de la démarche de réduction du risque à la source et aux plans de prévention des risques technologiques (pprt) dans les installations classées en application de la loi du 30 juillet 2003. xix, pp.61-103, 2014.

P. Leonelli, G. Bonvicini, and . Spadoni, Hazardous materials transportation: a risk-analysis-based routing methodology, Journal of Hazardous Materials, vol.71, issue.1-3, pp.283-300, 2000.
DOI : 10.1016/S0304-3894(99)00084-9

P. Leonelli, S. Bonvicini, and G. Spadoni, New detailed numerical procedures for calculating risk measures in hazardous materials transportation, Journal of Loss Prevention in the Process Industries, vol.12, issue.6
DOI : 10.1016/S0950-4230(99)00023-6

G. Nancy, J. L. Leveson, and . Stolzy, Safety analysis using petri nets, IEEE Transactions on Software Engineering, vol.13, issue.3, pp.386-84, 1987.

C. Lewis, C. Kevin, and . Murdock, Alternative means of redistributing catastrophic risk in a national risk-management system, The Financing of Catastrophe Risk, pp.51-92, 1999.

Q. Long and W. Zhang, An integrated framework for agent based inventory???production???transportation modeling and distributed simulation of supply chains, Information Sciences, vol.277, pp.567-581, 2014.
DOI : 10.1016/j.ins.2014.02.147

E. Kim, . Lowell, K. Kurt, and . Benke, Uncertainty and risk analysis in hydrological models for land-use management, Accuracy 2006 : International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, pp.740-749, 2006.

M. Charles, . Macal, J. Michael, and . North, Agent-based modeling and simulation, Winter simulation conference, pp.86-98, 2009.

N. Malleson, Using simulation to predict prospective burglary rates in leeds and vancouver, 7th National Crime Mapping Conference, pp.7-8, 2009.

P. Marhavilas, V. Koulouriotis, and . Gemeni, Risk analysis and assessment methodologies in the work sites : On a review, classification and comparative study of the scientific literature of the period, Journal of Loss Prevention in the Process Industries, pp.477-523, 2000.

E. Mast and . Van-kuik, Agent-based modelling for scenario development of offshore wind energy The Netherlands, p.93, 2007.

P. Mccauley-bell, B. Adedeji, and . Badiru, Fuzzy modeling and analytic hierarchy processing to quantify risk levels associated with occupational injuries. i. the development of fuzzy-linguistic risk levels. Fuzzy Systems, IEEE Transactions on, vol.4, issue.2, pp.124-131, 1996.

G. Mejía, C. Montoya, J. Cardona, and A. L. Castro, Petri nets and genetic algorithms for complex manufacturing systems scheduling, International Journal of Production Research, vol.50, issue.3, pp.791-803, 2012.
DOI : 10.1023/A:1019920324813

N. Melão and M. Pidd, A conceptual framework for understanding business processes and business process modelling, Information Systems Journal, vol.44, issue.2, pp.105-129, 2000.
DOI : 10.1108/00251749510085021

N. Metropolis and S. Ulam, The Monte Carlo Method, Journal of the American Statistical Association, vol.44, issue.247, pp.335-341, 1949.
DOI : 10.1080/01621459.1949.10483310

Y. Demazeau and J. Miiller, Decentralized artificial intelligence. Decentralised AI, pp.3-13, 1990.

H. Min and G. Zhou, Supply chain modeling: past, present and future, Computers & Industrial Engineering, vol.43, issue.1-2, pp.231-249, 2002.
DOI : 10.1016/S0360-8352(02)00066-9

K. Mock and J. Testa, An agent-based model of predator-prey relationships between transient killer whales and other marine mammals, p.93, 2007.

B. Montreuil, . Labarthe, . D?amours, . Roy, . Ferrarini et al., Simulation à base d?agents des systèmes de coordination et de planification des réseaux d?entreprises. La simulation pour la gestion des Steps of Fuzzy TOPSIS and AHP chaînes logistiques, Traité IC2, série systèmes automatisés, pp.227-260, 2008.

W. Kent and M. , Pipeline risk management manual : ideas, techniques, and resources, p.39, 2004.

J. Müller, Modélisation organisationnelle en systèmes multi-agents. 7eme école d?été de l?Association pour la Recherche Cognitive, p.86, 2000.

K. Ngo and C. , Etude et amelioration de l'organisation de la production de dispositifs medicaux steriles, p.84, 2009.
URL : https://hal.archives-ouvertes.fr/tel-00371165

R. Nguyen, Ministère de l?ecologie et du développement durable direction de l?eau 20, avenue de ségur?75302 paris 07 sp, p.17, 2005.

L. William, . Oberkampf, C. Jon, C. A. Helton, . Joslyn et al., Challenge problems : uncertainty in system response given uncertain parameters, Reliability Engineering & System Safety, vol.85, issue.1, pp.11-19, 2004.

A. Oggero, M. Darbra, . Munoz, J. Planas, and . Casal, A survey of accidents occurring during the transport of hazardous substances by road and rail, Journal of Hazardous Materials, vol.133, issue.1-3, pp.1-7, 2006.
DOI : 10.1016/j.jhazmat.2005.05.053

O. Pat and . Malley, Risk, uncertainty and government. Routledge, p.60, 2012.

S. Pagnon, Stratégies de modélisation des conséquences d'une dispersion atmosphérique de gaz toxique ou inflammable en situation d'urgence au regard de l'incertitude sur les données d'entrée, p.54

H. Pasman, . Jung, . Prem, X. Rogers, and . Yang, Is risk analysis a useful tool for improving process safety ? Journal of Loss Prevention in the Process Industries, pp.769-777, 2009.

G. Richard, W. Pearson, . Thuiller, B. Miguel, E. Araújo et al., Model-based uncertainty in species range prediction, Journal of Biogeography, vol.33, issue.10, pp.1704-1711, 2006.

P. Pederson, S. Dudenhoeffer, M. Hartley, and . Permann, Critical infrastructure interdependency modeling : a survey of us and international research, pp.1-20, 2006.

P. Perilhon, La Gestion des risques : Mthode MADS-MOSAR II, Editions Demos, p.27, 2007.

C. Adam and P. , Kommunikation mit automaten, p.84, 1962.

E. Gloria, . Phillips-wren, C. Lakhmi, and . Jain, Intelligent Decision Support Systems in Agent-Mediated Environments, p.92, 2005.

H. William and . Press, Numerical recipes 3rd edition : The art of scientific computing, p.82, 2007.

C. Ptolemaeus, System Design, Modeling, and Simulation : Using Ptolemy II. Ptolemy, p.82, 2014.

G. Purdy, Risk analysis of the transportation of dangerous goods by road and rail, Journal of Hazardous Materials, vol.33, issue.2, pp.229-259, 1993.
DOI : 10.1016/0304-3894(93)85056-K

G. Purdy, ISO 31000:2009-Setting a New Standard for Risk Management, Risk Analysis, vol.30, issue.6, pp.881-886, 2010.
DOI : 10.1111/j.1539-6924.2010.01442.x

J. Quelch, T. Ian, and . Cameron, Uncertainty representation and propagation in quantified risk assessment using fuzzy sets Journal of loss prevention in the process industries, pp.463-473, 1994.

S. Anand, . Rao, P. Michael, and . Georgeff, Modeling rational agents within a bdiarchitecture, KR, vol.91, pp.473-484, 1991.

C. Revelle, J. Cohon, and D. Shobrys, Simultaneous Siting and Routing in the Disposal of Hazardous Wastes, Transportation Science, vol.25, issue.2, pp.138-145, 1991.
DOI : 10.1287/trsc.25.2.138

A. Ronza, J. Vilchez, and J. Casal, Using transportation accident databases to investigate ignition and explosion probabilities of flammable spills, Journal of Hazardous Materials, vol.146, issue.1-2, pp.106-123, 2007.
DOI : 10.1016/j.jhazmat.2006.11.057

J. Rumbaugh, I. Jacobson, and G. Booch, Unified Modeling Language Reference Manual, The. Pearson Higher Education, p.79, 2004.

F. Frank, S. , and A. Chan, Economic evaluation of routing strategies for hazardous road shipments. Number 1020, p.65, 1985.

E. Abed and E. Safadi, Contribution à l'évaluation des risques liés au TMD (transport de matières dangereuses) en prenant en compte les incertitudes, pp.2015-53

J. Nicolás, A. Scenna, and . Cruz, Road risk analysis due to the transportation of chlorine in rosario city, Reliability Engineering & System Safety, vol.90, issue.1, pp.83-90, 2005.

N. Schieritz, M. Peter, and . Milling, Modeling the forest or modeling the trees a comparison of system dynamics and agent-based simulation, Proceedings of the 21st International Conference of the System Dynamics Society. Citeseer, p.85, 2003.

A. Kathy and . Seabrook, Global safety and health briefing, ASSE Professional Development Conference and Exhibition. American Society of Safety Engineers, p.40, 2008.

P. Serafini, Dynamic programming and minimum risk paths, European Journal of Operational Research, vol.175, issue.1, pp.224-237, 2006.
DOI : 10.1016/j.ejor.2005.03.042

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

W. Siler, J. James, and . Buckley, Fuzzy expert systems and fuzzy reasoning
DOI : 10.1002/0471698504

R. Sivakumar, M. Batta, and . Karwan, Establishing credible risk criteria for transporting extremely dangerous hazardous materials. Transportation of Dangerous Goods : Assessing the Risks, pp.335-342, 1993.
DOI : 10.1016/0167-6377(93)90034-e

A. Edward and . Suchman, A conceptual analysis of the accident phenomenon, Social Problems, vol.8, issue.3, pp.241-253, 1960.

C. Sun, A performance evaluation model by integrating fuzzy ahp and fuzzy topsis methods Expert systems with applications, pp.7745-7754, 2010.

B. Tilanus, Information systems in logistics and transportation, 1997.

J. Tixier, G. Dusserre, O. Salvi, and D. Gaston, Review of 62 risk analysis methodologies of industrial plants Journal of Loss Prevention in the process industries, pp.291-303, 2002.

A. M. Tomasoni, Modèles et méthodes d'évaluation et de gestion des risques appliquées aux systèmes de transport de marchandises dangereuses (TMD), reposant sur les nouvelles technologies de l'information et de la communication (NTIC), pp.45-52, 2010.

J. Tounsi, Modélisation pour la simulation de la chaîne logistique globale dans un environnement de production PME mécatroniques, pp.90-179, 2009.

J. Treuil, A. Drogoul, and J. Zucker, Modélisation et simulation à base d'agents : exemples commentés, outils informatiques et questions théoriques, p.78, 2008.

A. Troisi, V. Wong, A. Mark, and . Ratner, From The Cover: An agent-based approach for modeling molecular self-organization, Proceedings of the National Academy of Sciences of the United States of America, pp.255-260, 2005.
DOI : 10.1073/pnas.0408308102

D. Bruce and T. , Workbook of atmospheric dispersion estimates. US Government Printing Office, p.142, 1973.

H. Ulrich, A Simulation Platform for Multiagent Systems in Logistics, Operations Research Proceedings, pp.261-268, 1998.
DOI : 10.1007/978-3-642-58409-1_26

H. Koen, Z. Van-dam, L. Lukszo, A. Ferreira, and . Sirikijpanichkul, Planning the location of intermodal freight hubs : an agent based approach, Networking, Sensing and Control IEEE International Conference on, pp.187-192, 2007.

C. Van-den, R. Bosch, and . Weterings, Methods for the Calculation of Physical Effect : Due to Releases of Hazardous Materials (liquids and Gases) : Yellow Book. Director-General of Labour, p.54, 2005.

G. Jan-willem, . Van-der-pas, A. Vincent, . Marchau, E. Warren et al., Isa implementation and uncertainty : A literature review and expert elicitation study, Accident Analysis & Prevention, vol.48, pp.83-96, 2012.

D. Vose, Defining distributions from expert opinion Risk Analysis : A Quantitative Guide, pp.263-290, 2000.

J. Vrijling, S. Van-gelder, and . Ouwerkerk, Criteria for acceptable risk in the netherlands. infrastructure risk management processes : natural, accidental and deliberate hazards, ASCE, 2005. xv, p.41

N. Wagner and V. Agrawal, An agent-based simulation system for concert venue crowd evacuation modeling in the presence of a fire disaster, Expert Systems with Applications, vol.41, issue.6, pp.2807-2815, 2014.
DOI : 10.1016/j.eswa.2013.10.013

Y. Wang, M. Taha, and . Elhag, An adaptive neuro-fuzzy inference system for bridge risk assessment, Expert Systems with Applications, vol.34, issue.4, pp.3099-3106, 2008.
DOI : 10.1016/j.eswa.2007.06.026

J. Werny, Gefahrgut-Checklisten für Praxis und Unterweisung, p.14, 2004.

R. Wirth, B. Berthold, A. Krämer, and G. Peter, Knowledge-based support of system analysis for the analysis of Failure modes and effects, Engineering Applications of Artificial Intelligence, vol.9, issue.3, pp.219-229, 1996.
DOI : 10.1016/0952-1976(96)00014-0

M. Wooldridge, Agent-based software engineering, IEE Proceedings - Software Engineering, vol.144, issue.1, pp.26-37, 1997.
DOI : 10.1049/ip-sen:19971026

M. Wooldridge, An introduction to multiagent systems, p.86, 2009.

M. Wooldridge, R. Nicholas, and . Jennings, Intelligent agents : Theory and practice. The knowledge engineering review, pp.115-152, 1995.
DOI : 10.1007/3-540-58855-8

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

D. Gregory, F. A. Wyss, and . Durán, Obest : the object-based event scenario tree methodology, Sandia National Laboratories, p.93, 2001.

J. Yang, F. Li, J. Zhou, L. Zhang, L. Huang et al., A survey on hazardous materials accidents during road transport in China from 2000 to 2008, Journal of Hazardous Materials, vol.184, issue.1-3, pp.647-653, 2000.
DOI : 10.1016/j.jhazmat.2010.08.085

K. Paul, Y. , and C. Hwang, Multiple attribute decision making : an introduction, Sage publications, vol.104, p.162, 1995.

A. Lotfi and . Zadeh, Fuzzy sets, Information and control, vol.8, issue.3, pp.338-353, 1965.

Z. Edmundas-kazimieras-zavadskas, J. Turskis, and . Tamo?aitiene, Risk assessment of construction projects, Journal of Civil Engineering and Management, vol.16, issue.1, pp.33-46, 2010.
DOI : 10.3846/jcem.2010.03

O. Zeman, The dynamics and modeling of heavier-than-air, cold gas releases, Atmospheric Environment (1967), vol.16, issue.4, pp.741-751, 1967.
DOI : 10.1016/0004-6981(82)90391-2

J. Zhang, J. Hodgson, and E. Erkut, Using GIS to assess the risks of hazardous materials transport in networks, European Journal of Operational Research, vol.121, issue.2, pp.316-329, 2000.
DOI : 10.1016/S0377-2217(99)00220-9

X. Zhang, Q. Lu, T. Wu, R. Zhou, . Fox et al., Petri-net based applications for supply chain management : an overview Bus maintenance scheduling using multiagent systems, International Journal of Production Research Engineering Applications of Artificial Intelligence, vol.49187, issue.176, pp.3939-3961, 2004.

Z. Saman-aliari and S. Miremadi, A fuzzy-monte carlo simulation approach for fault tree analysis, Reliability and Maintainability Symposium , 2006. RAMS'06. Annual, pp.428-433, 2006.