Mixing optimal solutions

US9396163B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9396163-B2
Application numberUS-201214343956-A
CountryUS
Kind codeB2
Filing dateDec 5, 2012
Priority dateDec 22, 2011
Publication dateJul 19, 2016
Grant dateJul 19, 2016

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  5. First independent claim

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  7. Citations and related patents

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Abstract

Official abstract text for this publication.

This invention relates to a method, system and computer program product for selecting an optimized solution in a computerised multiple-constraint problem space, comprising: receiving a linear function for optimization; receiving a set of constraints for the linear function; determining a first optimal solution for the linear function and initial constraints using linear programming solver; creating a new set of constrains using the first optimal solution as a constraint in addition to the initial constraints; creating a new quadratic function by adding a quadratic objective of slack variables to the linear function; and determining a solution to the quadratic function and new constraints using a quadratic programming solver.

First claim

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The invention claimed is: 1. A method for selecting an optimized solution in a computerized multiple-constraint problem space, comprising: receiving, by a processor, a linear function for optimization; receiving, by the processor, a set of constraints for the linear function; determining, by the processor, a first optimal solution for the linear function and initial constraints using a linear programming solver; creating, by the processor, a new set of constrains using the first optimal solution as a constraint in addition to the initial constraints; creating, by the processor, a new quadratic function by adding a quadratic objective of slack variables to the linear function; and determining, by the processor, a solution to the quadratic function and new constraints using a quadratic programming solver. 2. A method according to claim 1 wherein the slack variable constraints have a default set of weights. 3. A method according to claim 2 wherein the slack variable constraints are based on one or more administrator or user determined cost coefficients. 4. A method according to claim 1 wherein the linear function can be an integer function. 5. A method of controlling a device using a method as according to claim 1 . 6. A method for selecting one or more optimized values in a computerized multiple-constraint problem space, comprising: receiving, by a processor, as inputs a first set of input values of a mixed integer programming component, a second set of input values of a linear programming component, and a cost-weighted set of squared slack variable constraints based on one or more user-determined cost coefficients; producing, by the processor, a first set of output values of said mixed integer programming component; producing, by the processor, a second set of output values of said linear programming component; creating, by the processor, a restricted solution space according to said first set of output values and said second set of output values; and selecting, by the processor, an optimized value from said restricted solution space by applying a further restriction based on said cost-weighted set of squared slack variable constraints based on said one or more user-determined cost coefficients. 7. A system comprising a processor configured to perform a method for selecting an optimized solution in a computerized multiple-constraint problem space, comprising, the method comprising: receiving, by the processor, a linear function for optimization; receiving, by the processor, a set of constraints for the linear function; determining, by the processor, a first optimal solution for the linear function and initial constraints using the linear programming solver; creating, by the processor, a new set of constrains using the first optimal solution as a constraint in addition to the initial constraints; creating, by the processor, a new quadratic function by adding a quadratic objective of slack variables to the linear function; and determining, by the processor, a solution to the quadratic function and new constraints using the quadratic programming solver. 8. A system according to claim 7 wherein the slack variable constraints have a default set of weights. 9. A system according to claim 8 wherein the slack variable constraints are based on said one or more administrator or user determined cost coefficients. 10. A system according to claim 7 wherein the linear function can be an integer function. 11. A computer program product comprising computer readable recording medium having computer readable code stored thereon for selecting an optimized solution in a computerized multiple-constraint problem space, said computer readable code which when loaded onto a computer system and executed performs the following steps: receiving a linear function for optimization; receiving a set of constraints for the linear function; determining a first optimal solution for the linear function and initial constraints using a linear programming solver; creating a new set of constrains using the first optimal solution as a constraint in addition to the initial constraints; creating a new quadratic function by adding a quadratic objective of slack variables to the linear function; and determining a solution to the quadratic function and new constraints using a quadratic programming solver. 12. A computer program product according to claim 11 wherein the slack variable constraints have a default set of weights. 13. A computer program product according to claim 12 wherein the slack variable constraints are based on one or more administrator or user determined cost coefficients.

Assignees

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Classifications

  • G06Q10/04Primary

    Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202) · CPC title

  • for solving equations {, e.g. nonlinear equations, general mathematical optimization problems (optimization specially adapted for a specific administrative, business or logistic context G06Q10/04)} · CPC title

  • Differential equations (using digital differential analysers G06F7/64) · CPC title

  • G06F17/12Primary

    Simultaneous equations {, e.g. systems of linear equations} · CPC title

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What does patent US9396163B2 cover?
This invention relates to a method, system and computer program product for selecting an optimized solution in a computerised multiple-constraint problem space, comprising: receiving a linear function for optimization; receiving a set of constraints for the linear function; determining a first optimal solution for the linear function and initial constraints using linear programming solver; crea…
Who is the assignee on this patent?
IBM
What technology area does this patent fall under?
Primary CPC classification G06Q10/04. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Jul 19 2016 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).