Optimizer - Revision history

Mnguyen at 16:33, 30 January 2012

2012-01-30T16:33:39Z

← Older revision		Revision as of 16:33, 30 January 2012
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	A list of available optimizers is found in <code>src/matlab/tools/Optimization/optimizers</code>. Note that some optimizers need some external code available in the extension pack (or the Matlab Optimization toolbox).		A list of available optimizers is found in <code>src/matlab/tools/Optimization/optimizers</code>. Note that some optimizers need some external code available in the extension pack (or the Matlab Optimization toolbox).

	A couple of example configurations are found [[Config:Optimizer\|here]]. These tags can be used in supported components as stated above. When a particular option is not given a sane default will be used. Full information about the several options can be found in the optimizer source code, implementation and corresponding papers.		A couple of '''example configurations''' are found [[Config:Optimizer\|here]]. These tags can be used in supported components as stated above. When a particular option is not given a sane default will be used. Full information about the several options can be found in the optimizer source code, implementation and corresponding papers.

	=== Add a custom optimizer ===		=== Add a custom optimizer ===

Icouckuy at 11:49, 2 October 2009

2009-10-02T11:49:50Z

← Older revision		Revision as of 11:49, 2 October 2009
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	The SUMO Toolbox contains a whole hierarchy of optimizers that can be used by several components (for instance the [[SampleSelector#~~OptimizeCriterion~~\| ~~OptimizeCriterion~~]] or the [[~~ModelBuilder~~#~~OptimizeModelBuilder~~\|OptimizerModelBuilder]]).		The SUMO Toolbox contains a whole hierarchy of optimizers that can be used by several components (for instance the [[Config:SampleSelector#expectedImprovement\|EGO algorithm]] or the [[Config:AdaptiveModelBuilder#krigingoptim\|OptimizerModelBuilder]]).

	A list of available optimizers is found in <code>src/matlab/tools/Optimization/optimizers</code>. Note that some optimizers need some external code available in the extension pack (or the Matlab Optimization toolbox).		A list of available optimizers is found in <code>src/matlab/tools/Optimization/optimizers</code>. Note that some optimizers need some external code available in the extension pack (or the Matlab Optimization toolbox).

Icouckuy at 11:47, 2 October 2009

2009-10-02T11:47:41Z

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 A list of available optimizers is found in <code>src/matlab/tools/Optimization/optimizers</code>. Note that some optimizers need some external code available in the extension pack (or the Matlab Optimization toolbox).
-A couple of example configurations are listed below. These tags can be used in supported components as stated above. When a particular option is not given a sane default will be used. Full information about the several options can be found in the optimizer source codee, implementation and corresponding papers.
+A couple of example configurations are found [[Config:Optimizer|here]]. These tags can be used in supported components as stated above. When a particular option is not given a sane default will be used. Full information about the several options can be found in the optimizer source code, implementation and corresponding papers.
 === Add a custom optimizer ===

Icouckuy: /* Add a custom optimizer */

2009-02-23T13:34:03Z

Add a custom optimizer

← Older revision		Revision as of 13:34, 23 February 2009
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	=== Add a custom optimizer ===		=== Add a custom optimizer ===
	In order to implement a new optimization algorithm one should only create one new class in <code>src/matlab/tools/Optimization/optimizers</code>. The class should be derived from the base class Optimizer and MUST implement at least the following functions ~~(for example implementations, please see the provided optimizers)~~:		In order to implement a new optimization algorithm one should only create one new class in <code>src/matlab/tools/Optimization/optimizers</code>. The class should be derived from the base class Optimizer and MUST implement at least the following functions:
	* A constructor accepting one parameter (the configuration xml tag) OR a varargin		* A constructor accepting one parameter (the configuration xml tag) OR a varargin
	* [this, x, fval] = optimize(this, arg )		* [this, x, fval] = optimize(this, arg)
	Accepts a function handle ~~to optimize~~ OR a SUMO model ~~that needs~~ to ~~be optimized~~. x and fval are the resulting optimum(s) and associated function value(s).		** Accepts a function handle OR a SUMO model to optimize. x and fval are the resulting optimum(s) and associated function value(s).
	In addition the following methods COULD be implemented if appropriate:		In addition the following methods COULD be implemented if appropriate:
	* When implementing a population-based optimization algorithm~~: size~~ = ~~getPopulationSize~~(this)		* size = getPopulationSize(this)
	* When the algorithm supports constraints~~: this = setInputConstraints( this, con )~~		** When implementing a population-based optimization algorithm
			* this = setInputConstraints( this, con )
			** When the algorithm supports constraints

	It is advised to copy a simple existing optimizer and work from there. For instance, DifferentialEvolution is a good starting point. The optimizer can be used like:		It is advised to copy a simple existing optimizer and work from there. For example implementations, please see the provided optimizers. For instance, DifferentialEvolution is a good starting point. The optimizer can be used like:
	<source lang="xml">		<source lang="xml">
	<Optimizer type="CLASSNAME">		<Optimizer type="CLASSNAME">

Icouckuy: /* Add a custom optimizer */

2009-02-23T13:24:58Z

Add a custom optimizer

← Older revision		Revision as of 13:24, 23 February 2009
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	=== Add a custom optimizer ===		=== Add a custom optimizer ===
	In order to implement a new optimization algorithm one should only create one new class in <code>src/matlab/tools/Optimization/optimizers</code>. The class should be derived from the base class Optimizer and MUST implement at least the following functions (for example implementations, please see the provided optimizers):		In order to implement a new optimization algorithm one should only create one new class in <code>src/matlab/tools/Optimization/optimizers</code>. The class should be derived from the base class Optimizer and MUST implement at least the following functions (for example implementations, please see the provided optimizers):
	- A constructor accepting one parameter (the configuration xml tag) OR a varargin		* A constructor accepting one parameter (the configuration xml tag) OR a varargin
	- [this, x, fval] = optimize(this, arg )		* [this, x, fval] = optimize(this, arg )
	Accepts a function handle to optimize OR a SUMO model that needs to be optimized. x and fval are the resulting optimum(s) and associated function value(s).		Accepts a function handle to optimize OR a SUMO model that needs to be optimized. x and fval are the resulting optimum(s) and associated function value(s).
	In addition the following methods COULD be implemented if appropriate:		In addition the following methods COULD be implemented if appropriate:
	- When implementing a population-based optimization algorithm: size = getPopulationSize(this)		* When implementing a population-based optimization algorithm: size = getPopulationSize(this)
	- When the algorithm supports constraints: this = setInputConstraints( this, con )		* When the algorithm supports constraints: this = setInputConstraints( this, con )

	It is advised to copy a simple existing optimizer and work from there. For instance, DifferentialEvolution is a good starting point. The optimizer can be used like:		It is advised to copy a simple existing optimizer and work from there. For instance, DifferentialEvolution is a good starting point. The optimizer can be used like:

Icouckuy at 11:05, 9 February 2009

2009-02-09T11:05:23Z

Show changes

Dgorissen at 16:36, 8 February 2009

2009-02-08T16:36:43Z

← Older revision		Revision as of 16:36, 8 February 2009
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	The SUMO Toolbox contains a whole hierarchy of optimizers that can be used by several components (for instance the [[SampleSelector#InfillSamplingCriterion\| InfillSamplingCriterion]] or the [[Add Modeling ~~Algorthm~~\|Model Builder]]).		The SUMO Toolbox contains a whole hierarchy of optimizers that can be used by several components (for instance the [[SampleSelector#InfillSamplingCriterion\| InfillSamplingCriterion]] or the [[Add Modeling Algorithm\|Model Builder]]).

	A list of available optimizers is found in <code>src/matlab/tools/Optimizer</code>.		A list of available optimizers is found in <code>src/matlab/tools/Optimizer</code>.

	If you want to add a new optimizer please see [[Add a new optimizer]].		If you want to add a new optimizer please see [[Add a new optimizer]].

Dgorissen at 16:36, 8 February 2009

2009-02-08T16:36:17Z

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	~~== Optimizer ==~~

	The SUMO Toolbox contains a whole hierarchy of optimizers that can be used by several components (for instance the [[SampleSelector#InfillSamplingCriterion\| InfillSamplingCriterion]] or the [[Add Modeling Algorthm\|Model Builder]]).		The SUMO Toolbox contains a whole hierarchy of optimizers that can be used by several components (for instance the [[SampleSelector#InfillSamplingCriterion\| InfillSamplingCriterion]] or the [[Add Modeling Algorthm\|Model Builder]]).

Dgorissen at 16:36, 8 February 2009

2009-02-08T16:36:05Z

← Older revision		Revision as of 16:36, 8 February 2009
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	== Optimizer ==		== Optimizer ==

	The SUMO Toolbox contains a whole hierarchy of optimizers that can be used by several components (for instance the [[SampleSelector#InfillSamplingCriterion\| InfillSamplingCriterion]]). ~~Currently the following optimization methods are supported:~~		The SUMO Toolbox contains a whole hierarchy of optimizers that can be used by several components (for instance the [[SampleSelector#InfillSamplingCriterion\| InfillSamplingCriterion]] or the [[Add Modeling Algorthm\|Model Builder]]).

	~~=== DirectOptimizer ===~~		A list of available optimizers is found in <code>src/matlab/tools/Optimizer</code>.
	~~DIviding RECTangles is a global optimization algorithm based on the divide & conqueror philosophy. It is quite efficient at finding accurate, global optimums~~ of ~~computationel cheap functions. It~~ is ~~one of the standard choices to optimize the [[SampleSelector#InfillSamplingCriterion\|expected improvement function]]~~.

	~~=== MatlabOptimizer ===~~		If you want to add a new optimizer please see [[Add a new optimizer]].
	~~This~~ optimizer is a ~~wrapper around Matlab's own optimization methods: fminunc and fmincon~~.

	~~=== CMAESOptimizer ===~~

	~~=== MatlabGA ===~~

	~~=== DifferentialEvolution ===~~

Dgorissen: /* Optimizer */

2008-07-25T12:04:23Z

Optimizer

← Older revision		Revision as of 12:04, 25 July 2008
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	=== MatlabOptimizer ===		=== MatlabOptimizer ===
	This optimizer is a wrapper around Matlab's own optimization methods: fminunc and fmincon.		This optimizer is a wrapper around Matlab's own optimization methods: fminunc and fmincon.

			=== CMAESOptimizer ===

			=== MatlabGA ===

			=== DifferentialEvolution ===