Difference between revisions of "Optimizer"
From SUMOwiki
Jump to navigationJump to search| (3 intermediate revisions by one other user not shown) | |||
| Line 1: | Line 1: | ||
| − | The SUMO Toolbox contains a whole hierarchy of optimizers that can be used by several components (for instance the [[SampleSelector# | + | 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). | ||
| − | A couple of example configurations are | + | 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 === | ||
| − | 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 | + | 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 | + | ** 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) |
| − | * When the algorithm supports constraints | + | ** 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"> | ||
Latest revision as of 17:33, 30 January 2012
The SUMO Toolbox contains a whole hierarchy of optimizers that can be used by several components (for instance the EGO algorithm or the OptimizerModelBuilder).
A list of available optimizers is found in src/matlab/tools/Optimization/optimizers. 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 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
In order to implement a new optimization algorithm one should only create one new class in src/matlab/tools/Optimization/optimizers. 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
- [this, x, fval] = optimize(this, arg)
- 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:
- size = getPopulationSize(this)
- 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 example implementations, please see the provided optimizers. For instance, DifferentialEvolution is a good starting point. The optimizer can be used like:
<Optimizer type="CLASSNAME">
<Option key="option1" value="1" />
<Option key="option2" value="2" />
...
</Optimizer>
