Data processing: financial – business practice – management – or co – Automated electrical financial or business practice or... – Finance
Reexamination Certificate
2006-10-17
2006-10-17
Bashore, Alain L. (Department: 1762)
Data processing: financial, business practice, management, or co
Automated electrical financial or business practice or...
Finance
C705S035000
Reexamination Certificate
active
07124105
ABSTRACT:
A genetic algorithm determines a plan for payment of payment obligations in accounts payable of a finance account. The genetic algorithm operates to satisfy certain objectives, including maximizing the minimum daily cash on hand in the finance account. A genome population including a number of vectors is generated. The genome population is modified using a genetic algorithm, until at least one vector represents a plan for the payment obligations such that payment of each payment obligation in accordance with the vector most nearly satisfies one or more objectives.
REFERENCES:
patent: 5126936 (1992-06-01), Champion et al.
patent: 5255345 (1993-10-01), Shaefer
patent: 5644727 (1997-07-01), Atkins
patent: 5761442 (1998-06-01), Barr et al.
patent: 5845266 (1998-12-01), Lupien et al.
patent: 5852811 (1998-12-01), Atkins
patent: 5875437 (1999-02-01), Atkins
patent: 5999918 (1999-12-01), Williams et al.
patent: 6012046 (2000-01-01), Lupien et al.
patent: 6055517 (2000-04-01), Friend
patent: 6078904 (2000-06-01), Rebane
patent: 6098051 (2000-08-01), Lupien et al.
patent: 6188992 (2001-02-01), French
patent: 6240399 (2001-05-01), Frank et al.
patent: 6393409 (2002-05-01), Young
patent: 6405179 (2002-06-01), Rebane
patent: 6484152 (2002-11-01), Robinson
patent: 6601044 (2003-07-01), Wallman
patent: 6606615 (2003-08-01), Jennings et al.
patent: 2001/0034662 (2001-10-01), Morris
patent: 2002/0013754 (2002-01-01), Frank et al.
patent: 2002/0091605 (2002-07-01), Labe, Jr. et al.
patent: 2003/0088492 (2003-05-01), Damschroder
patent: 2003/0233304 (2003-12-01), Dhurandhar et al.
patent: 2004/0030622 (2004-02-01), Ramos et al.
patent: 2004/0128219 (2004-07-01), Hilton
patent: WO 96/18162 (1996-06-01), None
patent: WO 98/44443 (1998-10-01), None
patent: WO 98/44444 (1998-10-01), None
patent: WO 00/38094 (2000-06-01), None
patent: WO 00/39734 (2000-07-01), None
patent: WO 03/017683 (2003-02-01), None
patent: WO 03/079150 (2003-09-01), None
Pacheco et al: “Cash Flow Planning and Optimization through genetic algorithms”; ICA, Rio de Janerio; 6 pages; NO DATE.
Cacho, Oscar et al., “A Genetic Algorithm Approach To Farm Investment,” The Australian Journal of Agricultural and Resource Economics (Sep. 1999), vol. 43, Issue 3, pp. 305-322.
Chen, Shu-Heng et al., “Option Pricing with Genetic Algorithms: The Case of European-Style Options,” Proceedings of the Seventh International Conference on Genetic Algorithms, Michigan State University (Jul. 19-23, 1997), pp. 704-711.
Gilli, Manfred et al., “Heuristic Approaches for Portfolio Optimization,” Computing in Economics and Finance 2000 [online], Jul. 5, 2000, [retrieved on May 30, 2002]. Retrieved from the Internet: <URL: http/fmwww.bc.edu/cef00/papers/paper289.pdf>.
Kallel, Leila et al., “Alternative Random Initialization in Genetic Algorithms,” Proceedings of the Seventh International Conference on Genetic Algorithms, Michigan State University (Jul. 19-23, 1997), pp. 268-275.
Mansini, Renata et al., “Heuristic Algorithms for the Portfolio Selection Problem With Minimum Transaction Lots,” European Journal of Operational Research 114 (1999), pp. 219-233.
Mehta, Kumar et al., “Combined Rules Learnt Using Genetic Algorithms for Financial Forecasting,” Proceedings of the Congress on Evolutionary Computation (CEC), Washington D.C. [online], Jun. 1999 [retrieved on May 30, 2002]. Retrieved from the Internet: <ULR: http://icarus.cc.uic.edu/˜kmehta1/CEC99.pdf>.
Neuneier, Ralph, “Optimal Asset Allocation Using Adaptive Dynamic Programming,” Advances in Neural Information Processing Systems (1996), vol. 8, pp. 952-958.
Noe, Thomas H. et al. “Corporate Financing: An Artificial Agent-Based Analysis,” source unknown (Mar. 2000), pp. 1-47.
Pacheco, Marco Aurélio et al., “Cash Flow Planning and Optimization Through Genetic Algorithms,” Computing in Economics and Finance 2000, Society for Computational Economics (2000) No. 333.
Sakanashi, Hidenori et al., “Adaptive Attention Control in Genetic Algorithm,” IPSJ Journal Abstract, vol. 38 No. 07-001 [online], May 24, 2001 [retrieved on Nov. 5, 2002]. Retrieved from the Internet: <ULR: http://www.ipsj.or.jp/members//Journal/Eng/3807/article001.htm>.
Tsutsui, Shigeyoshi et al., “A Real Coded Genetic Algorithm with an Explorer and an Exploiter Populations,” Proceedings of the Seventh International Conference on Genetic Algorithms, Michigan State University (Jul. 19-23, 1997), pp. 238-245.
Wall, Matthew, “Overview of Genetic Algorithms,” MIT Mechanical Engineering Department presentation on Introduction to Genetic Algorithms [online], date unknown [retrieved on Nov. 8, 2001]. Retrieved from the Internet: <ULR: http://lancet.mit.edu/˜mbwall/presentations/IntroToGAs/P001.html>.
Alander, Jarmo T., “An indexed Bibliography of Genetic Algorithms in Economics,” drafted May 18, 2000, Department of Information Technology and Production Economics, University of Vaasa, Report Series No. 94-1-ECO.
Bao, Paul et al, “A Hybrid Portfolio Theory Model Based on Genetic Algorithm and Vector Quantization,” Oct. 1998, 1998 Proceedings of IEEE Conference on Systems, Man and Cybernetics, San Diego, California, pp. 4301-4306.
Bedau, Mark A., et al, “Visualizing Waves of Evolutionary Activity of Alleles,” Jul. 13, 1999, Proceedings of the 1999 Genetic and Evolutionary Computation Conference Workshop Program, Orlando, Florida, pp. 96-98.
Butler, James M., et al, “EDDIE Beats the Bookies,” Dec. 15, 1995, Wiley InterScience Software—Practice & Experience, vol. 28, Issue 10 (Aug. 1998), pp. 1033-1043.
Chan, Man-Chung et al, “Genetic Algorithms in Multi-Stage Asset Allocation System,” Oct. 2002, 2002 Proceedings of IEEE International Conference on System, Man and Cybernetics, vol. 3, pp. 316-321.
Chen, Shu-Heng, “Evolutionary Computation in Financial Engineering: A Roadmap of GAs and GP,” date unknown, Financial Engineering News, vol. 2, No. 4 (Sep. 1998), 10 pages.
Chen, Shu-Heng, “On the Relevance of Genetic Programming to Evolutionary Economics,” 2001, Evolutionary Controversy in Economics Towards a New Method in Preference of Trans Discipline, Springer-Verlag, Tokyo, pp. 135-150.
Dempster, M. et al, “A Real-Time Adaptive Trading System Using Genetic Programming,” 2001, Quantitative Finance vol. 1, Institute of Physics Publishing, pp. 397-413.
Dhar, Vasant et al, Abstract of “Data Mining and Knowledge Discovery” (online), Oct. 2000, Kluwer Journals.
Dunis, Christian L. et al, Abstract of “Forecasting and Trading Currently Volatility: An Application of Recurrent Neural Regression and Model Combination” (online), Jun. 2002, Wiley InterScience Journal of Forecasting.
Foster, James A. et al, “Portfolio Selection with Genetic Algorithms,” Apr. 4, 1996, University of Idaho, Department of Computer Science Laboratory for Applied Logic, 13 pages.
Frick, Andreas, et al, “A Genetic-Based Approach for the Derivation of Trading Strategies on the German Stock Market,” 1996, Proceedings of 3rdInternational Conference on Neural Information Processing, Hong Kong (Sep. 24-27, 1996), pp. 776-770.
Frick, Andreas, et al, “Genetic-Based Trading Rules—A New Tool to Beat the Market With?,” 1996, Proceedings of 6thInternational AFIR Colloquium, Nürnberg (Oct. 1-3, 1996), vol. I/II, pp. 997-1018.
IBA, Hitoshi et al., “Using Genetic Programming to Predict Financial Data,” Sep. 1999, Proceedings of the Congress on Evolutionary Computation, vol. 1, pp. 244-251.
Jiang, Rui et al, “Discovering Investment Strategies in Portfolio Management: A Genetic Algorithm Approach,” Proceedings of the 9thInternational Conference on Neural Information Processing (Nov. 18-22, 2002), vol. 3, pp. 1206-1210.
Kai, Fu et al, “Traini
Bashore Alain L.
Fenwick & West LLP
Intuit Inc.
LandOfFree
Cash flow optimization using a genetic algorithm does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Cash flow optimization using a genetic algorithm, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Cash flow optimization using a genetic algorithm will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3687729