Method and system for solving integer programming and...

Data processing: artificial intelligence – Plural processing systems

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

C706S052000

Reexamination Certificate

active

07877333

ABSTRACT:
Discrete optimization problem are solved using an analog optimization device such as a quantum processor. Problems are solved using an objective function and at least one constraint corresponding to the discrete optimization problems. The objective function is converted into a first set of inputs and the at least one constraint is converted into a second set of inputs for the analog optimization device. A third set of inputs is generated which are indicative of at least one penalty coefficient. A final state of the analog optimization device corresponds to at least a portion of the solution to the discrete optimization problem.

REFERENCES:
patent: 6838694 (2005-01-01), Esteve et al.
patent: 7135701 (2006-11-01), Amin et al.
patent: 7230266 (2007-06-01), Hilton et al.
patent: 7253654 (2007-08-01), Amin
patent: 2001/0032694 (2001-10-01), Ishiyama
patent: 2004/0167753 (2004-08-01), Downs et al.
patent: 2005/0082519 (2005-04-01), Amin et al.
patent: 2005/0137959 (2005-06-01), Yan et al.
patent: 2005/0162302 (2005-07-01), Omelyanchouk et al.
patent: 2005/0224784 (2005-10-01), Amin et al.
patent: 2005/0250651 (2005-11-01), Amin et al.
patent: 2005/0256007 (2005-11-01), Amin et al.
patent: 2005/0273306 (2005-12-01), Hilton et al.
patent: 2006/0097747 (2006-05-01), Amin
patent: 2006/0147154 (2006-07-01), Thom et al.
patent: 2006/0225165 (2006-10-01), Maassen van den Brink et al.
patent: 2006/0248618 (2006-11-01), Berkley
patent: 1647924 (2006-04-01), None
Farhi et al., “Quantum Adiabatic Evolution Algorithms versus Simulated Annealing,” MIT-CTP #3228, arXiv:quant-ph/0201031 v1, pp. 1-16, Jan. 8, 2002.
Knysh et al., “Adiabatic Quantum Computing in Systems with Constant Inter-Qubit Couplings,” arXiv.org, arxiv:quant-ph/0511131, pp. 1-10, Nov. 15, 2005.
U.S. Appl. No. 11/765,361, filed Jun. 19, 2007, Macready et al.
U.S. Appl. No. 60/975,083, filed Sep. 25, 2007, Amin.
U.S. Appl. No. 11/932,248, filed Oct. 31, 2007, Coury et al.
U.S. Appl. No. 11/932,261, filed Oct. 31, 2007, Macready et al.
U.S. Appl. No. 12/017,995, filed Jan. 22, 2008, Harris.
U.S. Appl. No. 12/111,818, filed Apr. 29, 2008, Fan Tang et al.
U.S. Appl. No. 12/113,753, filed May 1, 2008, Johnson et al.
“A High-Level Look at Optimization: Past, Present and Future,” e-Optimization.Community, May 2000, pp. 1-5.
Aji et al., “The Generalized Distributive Law and Free Energy Minimization,” 10 pages, Proc. 39th Allerton Conf. Communications, Control, and Computing, 2001.
Allen et al., “Blue Gene: A vision for protein science using a petaflop supercomputer,”IBM Systems Journal 40(2): 310-327, 2001.
Blatter et al., “Design Aspects of Superconducting-phase Quantum Bits,”Physical Review B 63(174511):1-9, 2001.
Boros et al., “Pseudo-Boolean Optimization,”Rutcor Research Report, Rutgers University, pp. 1-84, Sep. 2001.
Boyer et al., “On the Cutting Edge: SimplifiedO(n) Planarity by Edge Addition,”Journal of Graph Algorithms and Applications 8(3):241-273, 2004.
Cadoli et al., “Combining Relational Algebra, SQL, Constraint Modelling and Local Search,” arXiv:cs/0601043v1 [cs.AI], pp. 1-30, Jan. 11, 2006.
Chinneck, “Finding a Useful Subset of Constraints for Analysis in an Infeasible Linear Program,”INFORMS Journal on Computing 9(2): 164-174, Spring 1997.
Dolan et al., “Optimization on the NEOS Server,”SIAM News 35(6): 1-5, Jul./Aug. 2002.
Feynman, “Simulating Physics with Computers,”International Journal of Theoretical Physics 21(6/7): 467-488, 1982.
Fourer et al., “Optimization as an Internet Resource,”INTERFACES 31(2): 130-150, Mar.-Apr. 2001.
Friedman et al., “Quantum superposition of distinct macroscopic states,”Nature 406: 43-46, Jul. 6, 2000.
Gutwenger et al., “Graph Drawing Algorithm Engineering with AGD,” in Diehl (ed.),Lecture Notes in Computer Science 2269. Revised Lectures on Software Visualization, International Seminar, Springer-Verlag, London, 2001, pp. 307-323.
Heckmann et al., “Optimal Embedding of Complete Binary Trees into Lines and Grids,” in Schmidt and Berghammer (eds.),Lecture Notes in Computer Science 570. Proceedings of the 17thInternational Workshop, Springer-Verlag, London 1991, pp. 25-35.
Il'ichev et al., “Continuous Monitoring of Rabi Oscillations in a Josephson Flux Qubit,”Physical Review Letters 91(9): 097906-1-097906-4, week ending Aug. 29, 2003.
Knysh et al., “Adiabatic Quantum Computing in Systems with Constant Inter-Qubit Couplings,” arXiv.org, URL=http://arxiv:quant-ph/0511131, pp. 1-10, Nov. 15, 2005.
Kochenberger et al., “A unified modeling and solution framework for combinatorial optimization problems,”OR Spectrum 26: 237-250, 2004.
Landauer, “Hybrid Digital/Analog Computer Systems,”Computer, pp. 15-24, Jul. 1976.
Makhlin et al., “Quantum-state engineering with Josephson-junction devices,”Reviews of Modern Physics 73(2): 357-400, Apr. 2001.
Mitchell et al., “Model Expansion as a Framework for Modelling and Solving Search Problems,” SFU Computing Science Technical Report TR 2006-24, pp. 1-42, 2006.
Mooij et al., “Josephson Persistent-Current Qubit,”Science285: 1036-1039, Aug. 13, 1999.
Mutzel, “Optimization in Graph Drawing,” in Pardalos and Resende (eds.),Handbook of Applied Optimization, Oxford University Press, New York, 2002, pp. 967-977.
Nielsen et al.,Quantum Computation and Quantum Information, Cambridge University Press, Cambridge, 2000, “7.8 Other implementation schemes,” pp. 343-345.
Orlando et al., “Superconducting Persistent-current Qubit,”Physical Review B 60(22):398-413, Dec. 1, 1999.
Rosenberg, “Reduction of bivalent maximization to the quadratic case,”Cahier du Centre d'Etudes de Recherche Operationelle 17: 71-74, 1975.
Rubin et al., “Hybrid Computation 1976 and Its Future,”Computer, pp. 37-46, Jul. 1976.
Shields, Jr. et al., “Area Efficient Layouts of Binary Trees on One, Two Layers,” Parallel and Distributed Computing and Systems, Anaheim, California, 2001.
Shirts et al., “Computing: Screen Savers of the World Unite!,”Science Online 290(5498): 1903-1904, Dec. 8, 2000.
Shor, “Introduction to Quantum Algorithms,” AT&T Labs—Research, arXiv:quant-ph/0005003 v2, pp. 1-17, Jul. 6, 2001.
Wah et al., “The Theory of Discrete Lagrange Multipliers for Nonlinear Discrete Optimization,” J. Jaffar (Ed.): CP'99,LNCS 1713: 28-42, 1999.
Wu, “The Theory and Applications of Discrete Constrained Optimization Using Lagrange Multipliers,” Thesis submitted in the Graduate College of the University of Illinois at Urbana-Champaign, pp. iii-203, 2000.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Method and system for solving integer programming and... does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Method and system for solving integer programming and..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Method and system for solving integer programming and... will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-2645185

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.