WO2007055927A3 - Statistical optimizer - Google Patents
Statistical optimizer Download PDFInfo
- Publication number
- WO2007055927A3 WO2007055927A3 PCT/US2006/041863 US2006041863W WO2007055927A3 WO 2007055927 A3 WO2007055927 A3 WO 2007055927A3 US 2006041863 W US2006041863 W US 2006041863W WO 2007055927 A3 WO2007055927 A3 WO 2007055927A3
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- criteria
- met
- fitness
- vector
- vectors
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
Abstract
Methods and apparatus for rapidly converging on a solution in a large ragged search space, such as NP-Complete space, where the solution is good but not necessarily the most optimum are provided First, Frequency and Neighborhood Tables are built (103) as seen in Figure 1 Next, vectors are instantiated (105) and a Fitness Engine evaluates the fitness of each vector (107) The N% of vectors with the lowest fitness are discarded (109) This is repeated until the criteria are met (111) After the criteria are met, the optional solver/optimizer may be used (113) If it is used (1 15), it is used until the criteria are met (117) Then the overcall criteria are checked, if they are not met, the method returns to the beginning (119) If the criteria are met, the vector with the best fitness is selected (121), and the optional optimization is performed on that vector (123)
Applications Claiming Priority (4)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US73346805P | 2005-11-03 | 2005-11-03 | |
US60/733,468 | 2005-11-03 | ||
US34091906A | 2006-01-26 | 2006-01-26 | |
US11/340,919 | 2006-01-26 |
Publications (2)
Publication Number | Publication Date |
---|---|
WO2007055927A2 WO2007055927A2 (en) | 2007-05-18 |
WO2007055927A3 true WO2007055927A3 (en) | 2009-05-07 |
Family
ID=38023766
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/US2006/041863 WO2007055927A2 (en) | 2005-11-03 | 2006-10-25 | Statistical optimizer |
Country Status (1)
Country | Link |
---|---|
WO (1) | WO2007055927A2 (en) |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109085804A (en) * | 2018-07-17 | 2018-12-25 | 昆明理工大学 | It is a kind of for electronic product multiplexing factory manufacture process Optimization Scheduling |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5272638A (en) * | 1991-05-31 | 1993-12-21 | Texas Instruments Incorporated | Systems and methods for planning the scheduling travel routes |
US20040143725A1 (en) * | 2002-08-05 | 2004-07-22 | Edwin Addison | Knowledge-based methods for genetic network analysis and the whole cell computer system based thereon |
-
2006
- 2006-10-25 WO PCT/US2006/041863 patent/WO2007055927A2/en active Application Filing
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5272638A (en) * | 1991-05-31 | 1993-12-21 | Texas Instruments Incorporated | Systems and methods for planning the scheduling travel routes |
US20040143725A1 (en) * | 2002-08-05 | 2004-07-22 | Edwin Addison | Knowledge-based methods for genetic network analysis and the whole cell computer system based thereon |
Also Published As
Publication number | Publication date |
---|---|
WO2007055927A2 (en) | 2007-05-18 |
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