Concurrent consideration of evacuation safety and productivity in manufacturing facility planning using multi-paradigm simulations

Computers and Industrial Engineering

Volumn 61, Issue 4, 2011, Pages 1135-1148

  Vasudevan, Karthik ^a   Son, Young Jun ^a  

^a University of Arizona   (United States)

Author keywords

Agent based simulation; BDI; Emergency management; Layout planning

Indexed keywords

AGENT BASED; AGENT BASED SIMULATION; AGENT FRAMEWORK; BDI; BELIEF-DESIRE-INTENTIONS; CROWD SIMULATION; EMERGENCY MANAGEMENT; HUMAN-IN-THE-LOOP; IMMERSIVE VIRTUAL REALITY; LAYOUT PLANNING; MANUFACTURING FACILITY; MANUFACTURING PLANT; MULTI-PARADIGM SIMULATION; PRODUCTIVITY PERFORMANCE; RULE BASED; SAFE EVACUATION; SAFETY PERFORMANCE INDICATORS; SAFETY STANDARD;

AUTOMOBILE ENGINE MANUFACTURE; BENCHMARKING; DISCRETE EVENT SIMULATION; EXPERIMENTS; MANUFACTURE; PRODUCTIVITY; RISK MANAGEMENT; VIRTUAL REALITY;

INDUSTRIAL APPLICATIONS;

EID: 80054963659     PISSN: 03608352     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cie.2011.07.003     Document Type: Article

References (33)

1. E. Bonabeau, and C. Meyer Swarm intelligence: A whole new way to think about business Harvard Business Review 2001 107 114
2. Bouvier, E., & Guillotaeu, P. (1996). Crowd simulation in immersive space management. In Proceedings of the eurographics workshop on virtual environments and scientific visualization, pp. 104-110.
3. M. Bratman Intention, plans and practical reason 1987 Harvard University Press Cambridge
4. Braun, A., Musse, S. R., De Oliveira, L. P. L., & Bodmann, B. E. J. (2003). Modeling individual behaviors in a crowd simulation. In Proceedings of the 16th international conference on computer animation and social agents (pp. 143-148).
5. J.L. Casti Reality rules I: Picturing the world in mathematics 1997 John Wiley & Sons New York
6. Cumo, M., & Naviglo, A. (1989). Safety design criteria for industrial plants (Vol. II). New York: CRC Press.
7. P. Dagum, and M. Luby Approximating probabilistic inference in Bayesian belief networks is NP-hard Artificial Intelligence 60 1993 141 153 (Pubitemid 23622908)
8. Davidsson, P. (2002). Agent based social simulation: A computer science view. Journal of Artificial Societies and Social Simulation, 5(1).
9. R. Fikes, and N.J. Nilsson STRIPS: A new approach to application of theorem proving to problem solving Artificial Intelligence 2 1971 189 208
10. Hamagami, T., Hirata, H. (2003). Method of crowd simulation using multiagent on cellular automata. In Proceedings of international conference on intelligent agent technology, pp. 46-52.
11. Harris, J. H. (1981). Psychological stress and task performance. University of Kentucky.
12. S. Heragu Facilities design 1997 PWS Publishing Boston
13. Jain, S., & McLean, C. R. (2006). A concept prototype for integrated gaming and simulation for incident management. In Proceedings of the 37th winter simulation conference (pp. 493-500).
14. G. Keinan Decision making under stress, scanning of alternatives under controllable and uncontrollable threats Journal of Personality and Social Psychology 52 3 1987 639 644
15. Kelton, D., Sadowski, R. P., & Sadowski, D. A. (2002). Simulation with arena. McGraw-Hill.
16. D.A. Kinny, C.F. Bond, C.D. Mohr, and E.M. Horn Do we know how much people like one another Journal of Personality and Social Psychology 71 5 1996 928 936 (Pubitemid 126420767)
17. J.K. Lathrop Life safety code handbook 1991 NFPA Quincy
18. Linville, J. S., & Petraglia, J. S. (1989). Industrial fire hazards handbook: A guide to fire protection in industry. National Fire Protection Association (NFPA).
19. G.F. Loewenstien, E.U. Weber, C.K. Hsee, and N. Welch Risk as feelings Psychological Bulletin 127 2 2001 267 286 (Pubitemid 33696171)
20. Lucas, A., & Goss, S. (1999). The potential for intelligent software agents in defence simulation. In Proceedings of information decision and control (pp. 579-583).
21. Macal, C. M., North, M. J. (2005). Tutorial on agent-based modeling and simulation. In Proceedings of the winter simulation conference (pp. 2-16).
22. Norling, E. (2003). Capturing the quake player: Using a BDI agent to model human behavior. In Proceedings of the second international joint conference on autonomous agents and multiagent systems (pp. 1080-1081).
23. Pape, D. (1997). CAVE library features. Invited Talk, Visual Supercomputing Institute.
24. Rao, A. S., Georgeff, M. P. (1998). Decision procedures for BDI logics. Journal of Logic Computation, 1711-1738.
25. S. Ressler Applying virtual reality to manufacturing 1994 NIST Document Gaithersburg
26. C.W. Reynolds Flocks, herds and schools: A distributed behavior model Computer Graphics 21 4 1987 25 34
27. R.C. Schroll Industrial fire protection handbook 2002 CRC Press New York
28. Sutherland, I. (1965). The ultimate display. In Proceedings of the IFIP congress (pp. 506-508).
29. Takahashi, T., Mizuta, H. (2006). Efficient agent based simulation framework for multi-node super computers. In Proceedings of the winter simulation conference (pp. 919-925).
30. S.E. Taylor, B.P. Buunk, and L.G. Aspinwall Social comparison, stress and coping Personality and Social Psychology Bulletin 16 1 1990 74 89
31. N. Ye, P. Banarjee, A. Banarjee, and F. Dech A comparative study of assembly planning in traditional and virtual environments IEEE Transactions on Systems, Man and Cybernetics 29 4 1999 546 555 (Pubitemid 32081628)
32. Y. Yuan, and M.J. Shaw Induction of fuzzy decision trees Fuzzy Sets and Systems 69 1995 125 139
33. X. Zhao, and Y.J. Son BDI based human decision making model in automated manufacturing system International Journal of Modeling and Simulation 28 3 2008 347 356