US 8,572,004 B2Granted

Space solution search

AssigneeInternational Business Machines Corporation

InventorsMoises Cases, Jinwoo Choi, Bhyrav M. Mutnury, Navraj Singh

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Abstract

A statistical approach can be used to efficiently supply an initial population that provides a good global description of a design space. The SI based simulation can then find a global best design within a reduced number of simulations. The statistical approach can be utilized to determine a plurality of potential best and worst case designs from a design space. The plurality of potential best and worst case designs from the design space seed or prime a SI based simulation. The best case designs are based on design parameters than can be controlled. The worst case designs are based on design parameters than cannot be controlled due. SI based simulations can then be run on the best case designs with respect to the worst case designs to determine probability of failure of the best case design.

Claims17

Dependent claims

A method comprising:

performing a design of experiment based statistical analysis on a design space defined by a plurality of values for a plurality of parameters;
generating a plurality of potential best and worst cases for a design based, at least in part, on said performing the design of experiment based statistical analysis on the design space defined by the plurality of values for the plurality of parameters;
seeding a population of a swarm intelligence based simulation of the design with the plurality of potential best and worst cases for the design,
wherein said seeding the population of the swarm intelligence based simulation of the design with the plurality of potential best and worst cases for the design comprises,
setting personal bests of each of a first plurality of simulation agents to one of the plurality of potential best cases;
setting a collective best for the first plurality of simulation agents to a best of the plurality of potential best cases;
setting personal worsts of each of a second plurality of simulation agents to one of the plurality of potential worst cases;
and
setting a collective worst for the second plurality of simulation agents to a worst of the plurality of potential worst cases, wherein the swarm intelligence based simulation employs the first and the second plurality of simulation agents;
and
generating an overall best case of the design and an overall worst case of the design based, at least in part, on an output of the swarm intelligence simulation.

8 more elements

A computer program product for design space search, the computer program product comprising:

a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising:
computer readable program code configured to,
perform a design of experiment based statistical analysis on a design space defined by a plurality of values for a plurality of parameters;
generate a plurality of potential best and worst cases for a design based, at least in part, on performing the design of experiment based statistical analysis on the design space defined by the plurality of values for the plurality of parameters;
seed a population of a swarm intelligence based simulation of the design with the plurality of potential best and worst cases for the design, wherein the computer readable program code being configured to seed the population of the swarm intelligence based simulation of the design with the plurality of potential best and worst cases for the design comprises the computer readable program code being configured to,
set personal bests of each of a first plurality of simulation agents to one of the plurality of potential best cases;
set a collective best for the first plurality of simulation agents to a best of the plurality of potential best cases;
set personal worsts of each of a second plurality of simulation agents to one of the plurality of potential worst cases;
and
set a collective worst for the second plurality of simulation agents to a worst of the plurality of potential worst cases, wherein the swarm intelligence based simulation employs the first and the second plurality of simulation agents;
and
generate an overall best case of the design and an overall worst case of the design based, at least in part, on an output of the swarm intelligence simulation.

9 more elements

A computer program product for optimizing design space search efficiency, the computer program product comprising:

a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising:
computer readable program code configured to,
prime a swarm intelligence based simulation with output from a design of experiment based statistical analysis performed with a plurality of values for a plurality of parameters that define a space for a design;
and
generate a representation of a recommended design based, at least in part, on a set of the plurality of values determined by the swarm intelligence simulation, wherein the computer readable program code being configured to generate the representation of the recommended design based, at least in part, on the set of the plurality of values determined by the swarm intelligence simulation comprises the computer readable program code being configured to,
set the plurality of best cases as bests of a first plurality of simulation agents;
set a collective best for the first plurality of simulation agents to a best of the plurality of best cases;
set the plurality of worsts as personal worsts of a second plurality of simulation agents;
and
set a collective worst for the second plurality of simulation agents to a worst of the plurality of worst cases, wherein the swarm intelligence based simulation employs the first and the second plurality of simulation agents to search the space.

7 more elements

An apparatus comprising:

a process unit;
a network interface;
and
a simulation unit operable to,
perform a design of experiment based statistical analysis on a design space defined by a plurality of values for a plurality of parameters;
generate a plurality of potential best and worst cases for a design based, at least in part, on performing the design of experiment based statistical analysis on the design space defined by the plurality of values for the plurality of parameters;
seed a population of a swarm intelligence based simulation of the design with the plurality of potential best and worst cases for the design, wherein the simulation unit being operable to seed the population of the swarm intelligence based simulation of the design with the plurality of potential best and worst cases for the design comprises the simulation unit being operable to,
set personal bests of each of a first plurality of simulation agents to one of the plurality of potential best cases;
set a collective best for the first plurality of simulation agents to a best of the plurality of potential best cases;
set personal worsts of each of a second plurality of simulation agents to one of the plurality of potential worst cases;
and
set a collective worst for the second plurality of simulation agents to a worst of the plurality of potential worst cases, wherein the swarm intelligence based simulation employs the first and the second plurality of simulation agents;
and
generate an overall best case of the design and an overall worst case of the design based, at least in part, on an output of the swarm intelligence simulation.

11 more elements

Dependencies are inferred from the claim text.

Facts

Application: 12/649,064Filed 29 Dec 2009
Published: US 2011/0161055 A130 Jun 2011
Granted: 29 Oct 2013
Term ends: Not estimatedThe source records don’t support an estimate.

Classification5 codes

G06N 3/126
Using genetic models: evolutionary algorithms, e.g. genetic algorithms or genetic programming
G06F 30/20
Computer-aided design [CAD]: design optimisation, verification or simulation
G06F 2111/08
Details relating to CAD techniques: probabilistic or stochastic CAD
G06N
AI and machine learning

Family

US 2011/0161055 A1Pre-grant publication · published 30 Jun 2011
US 8,572,004 B2This patent

From the US filing history. Foreign family members aren’t listed.

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