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SIMULATION OPTIMIZATION: APPLICATIONS IN RISK MANAGEMENT

MARCO BETTER

OptTek Systems, Inc., 1919 Seventh Street, Boulder, Colorado 80302, USA

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FRED GLOVER

OptTek Systems, Inc., 1919 Seventh Street, Boulder, Colorado 80302, USA

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GARY KOCHENBERGER

University of Colorado Denver, 1250 14th Street, Suite 215, Denver, Colorado 80202, USA

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, and

HAIBO WANG

Texas A&M International University, Laredo, TX 78041, USA

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https://doi.org/10.1142/S0219622008003137Cited by:58 (Source: Crossref)

Abstract

Simulation optimization is providing solutions to important practical problems previously beyond reach. This paper explores how new approaches are significantly expanding the power of simulation optimization for managing risk. Recent advances in simulation optimization technology are leading to new opportunities to solve problems more effectively. Specifically, in applications involving risk and uncertainty, simulation optimization surpasses the capabilities of other optimization methods not only in the quality of solutions but also in their interpretability and practicality. In this paper, we demonstrate the advantages of using a simulation optimization approach to tackle risky decisions, by showcasing the methodology on two popular applications from the areas of finance and business process design.

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References

D. Vose , Risk Analysis: A Quantitative Guide ( John Wiley and Sons , Chichester , 2000 ) . Google Scholar
M. Fukushima, Int. J. Inform. Tech. Decis. Making 5(4), 623 (2006), DOI: 10.1142/S0219622006002192. Link, Web of Science, Google Scholar
H. Eskandari and L. Rabelo, Int. J. Inform. Tech. Decis. Making 6(1), 177 (2007), DOI: 10.1142/S0219622007002356. Link, Web of Science, Google Scholar
R. Dembo, Ann. Oper. Res. 30, 63 (1991), DOI: 10.1007/BF02204809. Web of Science, Google Scholar
P. Kouvelis and G. Yu, Robust Discrete Optimization and Its Applications (Kluwer, Dordrecht, Netherlands, 1997) pp. 8–29. Google Scholar
J. P. Kelly, INFORMS J. Comput. 14(3), 223 (2002), DOI: 10.1287/ijoc.14.3.223.108. Web of Science, Google Scholar
F. Glover and M. Laguna , Tabu Search ( Kluwer , Norwell, MA , 1997 ) . Google Scholar
F. Glover, M. Laguna and R. Martí, Control Cybernet. 29(3), 653 (2000). Web of Science, Google Scholar
W. J. Haskett , Optimal appraisal well location through efficient uncertainty reduction and value of information techniques , Proc. Society of Petroleum Engineers Annual Technical Conference and Exhibition ( 2003 ) . Google Scholar
W. J. Haskett , M. Better and J. April , Practical optimization: Dealing with the realities of decision management , Proc. Society of Petroleum Engineers Annual Technical Conference and Exhibition ( 2004 ) . Google Scholar
H. Markowitz, J. Finance 7(1), 77 (1952), DOI: 10.2307/2975974. Web of Science, Google Scholar
J. April, F. Glover and J. P. Kelly, Portfolio optimization for capital investment projects, Proc. 2002 Winter Simulation Conference, eds. S. Chicket al. (2002) pp. 1546–1554. Google Scholar
J. April, F. Glover and J. P. Kelly, Optfolio — A simulation optimization system for project portfolio planning, Proc. 2003 Winter Simulation Conference, eds. S. Chicket al. (2003) pp. 301–309. Google Scholar
S. Benninga and Z. Wiener, Math. Educ. Res. 7(4), 1 (1998). Web of Science, Google Scholar