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OptQuest software tutorial: portfolio optimization for capital investment projects

Published: 08 December 2002 Publication History

Abstract

The new portfolio optimization engine, OptFolio™, simultaneously addresses financial return goals, catastrophic loss avoidance, and performance probability. The innovations embedded in OptFolio enable users to confidently design effective plans for achieving financial goals, employing accurate analysis based on real data. Traditional analysis and prediction methods are based on mean variance analysis -- an approach known to be faulty. OptFolio takes a much more sophisticated and strategic direction. State-of-the-art technology integrates optimization and simulation techniques and a new surface methodology based on linear programming into a global system that guides a series of evaluations to reveal truly optimal investment scenarios. OptFolio is currently being used to optimize project portfolio performance in oil and gas applications and in capital allocation and budgeting for investments in technology.

References

[1]
Barr, R. S. 2000a. "Neural Network Design and Training by Adaptive Polynomial Column Generation: A New (LP)-Optimization Approach", Technical Report rsb51, Southern Methodist University.
[2]
Barr, R. S. 2000b. "Non-linear Discrimination by Adaptive Polynomial Column Generation", Technical Report rsb52, Southern Methodist University.
[3]
Glover, F. 1990. "Improved Linear Programming Models for Discriminant Analysis", Decision Sciences, Vol. 21, pp. 771--785.
[4]
Glover, F. 1996. "Tabu Search and Adaptive Memory Programming: Advances, Applications and Challenges", Interfaces in Computer Science and Operations Research, R. Barr, R. Helgason and J. Kennington (eds.) Kluwer Academic Publishers, pp. 1--75.
[5]
Glover, F., J. Kelly, and M. Laguna. 1999. "New Advances Wedding Simulation and Optimization", in the Proceedings of WSC'99, David Kelton, Ed.
[6]
Glover, F. and M. Laguna. 1997. Tabu Search, Kluwer Academic Publishers.
[7]
Glover, F. and M. Laguna. 1997a. "General Purpose Heuristics for Integer Programming --- Part I", Journal of Heuristics, vol. 2, no. 4, pp. 343--358.
[8]
Glover, F. and M. Laguna. 1997b. "General Purpose Heuristics for Integer Programming --- Part II", Journal of Heuristics, vol. 3, no. 2, pp. 161--179.
[9]
Glover, F., M. Laguna, and R. Marti. 2000. "Fundamentals of scatter search and path relinking", Control and Cybernetics, Vol. 29, No. 3, 653--684.
[10]
Kelly, J., B. Rangaswamy, and J. Xu. 1996. "A Scatter-Search-Based Learning Algorithm for Neural Network Training", Journal of Heuristics, vol. 2, pp. 129--146.
[11]
Markowitz, H. 1952. "Portfolio Selection", The Journal of Finance, vol. VII, no. 1, pp. 77--91.
[12]
McMillan, C., M. C. Mozer, and P. Smolensky. 1992. "Rule Induction Through a Combination of Symbolic and Subsymbolic Processing." in Advances in Neural Information Processing Systems 4, S. Hanson, L. Lippman, and L. Giles, (Eds.) Morgan Kaufmann.
[13]
McVean, J. R. 2000. "The Significance of Risk Definition on Portfolio Selection", paper presented at the 2000 SPE Annual Technical Conference and Exhibition, Dallas, TX.
[14]
Roy, A. 2001. "A New Learning Theory and Polynomial time Autonomous Learning Algorithms for Generating Radial Basis Function (RBF) Networks", in Radial Basis Function Neural Networks 1: Recent Developments in Theory and Applications, Howlett, R. J. and Jain, L. C. (Eds.) Physica Verlag, Chapter 10, pp. 253--280.
[15]
Roy, A., S. Govil, and R. Miranda. 1995. "An Algorithm to Generate Radial Basis Function (RBF)-like Nets for Classification Problems", Neural Networks, Vol. 8, No. 2, pp. 179--202.

Cited By

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  • (2017)Single and multi-objective parameter estimation of a military personnel system via simulation optimizationProceedings of the 2017 Winter Simulation Conference10.5555/3242181.3242536(1-12)Online publication date: 3-Dec-2017
  • (2016)Scenario and Robust Optimization in Risk ManagementInternational Journal of Risk and Contingency Management10.4018/IJRCM.20161001035:4(27-41)Online publication date: 1-Oct-2016
  • (2004)New advances and applications for marrying simulation and optimizationProceedings of the 36th conference on Winter simulation10.5555/1161734.1161756(80-86)Online publication date: 5-Dec-2004

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Published In

cover image ACM Conferences
WSC '02: Proceedings of the 34th conference on Winter simulation: exploring new frontiers
December 2002
2143 pages
ISBN:0780376153
  • General Chair:
  • Jane L. Snowdon,
  • Program Chair:
  • John M. Charnes

Sponsors

  • INFORMS/CS: Institute for Operations Research and the Management Sciences/College on Simulation
  • IIE: Institute of Industrial Engineers
  • ASA: American Statistical Association
  • ACM: Association for Computing Machinery
  • SIGSIM: ACM Special Interest Group on Simulation and Modeling
  • IEEE/CS: Institute of Electrical and Electronics Engineers/Computer Society
  • NIST: National Institute of Standards and Technology
  • (SCS): The Society for Modeling and Simulation International
  • IEEE/SMCS: Institute of Electrical and Electronics Engineers/Systems, Man, and Cybernetics Society

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Winter Simulation Conference

Publication History

Published: 08 December 2002

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WSC02
Sponsor:
  • INFORMS/CS
  • IIE
  • ASA
  • ACM
  • SIGSIM
  • IEEE/CS
  • NIST
  • (SCS)
  • IEEE/SMCS
WSC02: Winter Simulation Conference 2002
December 8 - 11, 2002
California, San Diego

Acceptance Rates

WSC '02 Paper Acceptance Rate 166 of 185 submissions, 90%;
Overall Acceptance Rate 3,413 of 5,075 submissions, 67%

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Cited By

View all
  • (2017)Single and multi-objective parameter estimation of a military personnel system via simulation optimizationProceedings of the 2017 Winter Simulation Conference10.5555/3242181.3242536(1-12)Online publication date: 3-Dec-2017
  • (2016)Scenario and Robust Optimization in Risk ManagementInternational Journal of Risk and Contingency Management10.4018/IJRCM.20161001035:4(27-41)Online publication date: 1-Oct-2016
  • (2004)New advances and applications for marrying simulation and optimizationProceedings of the 36th conference on Winter simulation10.5555/1161734.1161756(80-86)Online publication date: 5-Dec-2004

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