| Version 2.0 (R14SP3) Genetic Algorithm and Direct Search Toolbox™ Software Release Notes | |
This table summarizes what's new in version 2.0 (R14SP3):
| New Features and Changes | Version Compatibility Considerations | Fixed Bugs and Known Problems | Related Documentation at Web Site |
|---|---|---|---|
Yes | No | Bug Reports Includes fixes | None |
New features and changes introduced in this version are organized by these topics:
Previously, the genetic algorithm solver only solved unconstrained optimization problems, and the pattern search solver solved unconstrained optimization problems as well as those with linear constraints and bounds. Now, both solvers have to ability to solve general nonlinear optimization problems with linear constraints, bounds, and nonlinear constraints by accepting a nonlinear constraint function. The M-file for the nonlinear constraint function is accepted as an input argument at the command line for both the ga and patternsearch functions, as well as in the Constraints panel of psearchtool and gatool.
The GPS algorithm is the pattern search algorithm implemented in previous versions of the toolbox. The MADS algorithm is a modification of the GPS algorithm. The algorithms differ in how the set of points forming the mesh is computed. The GPS algorithm uses fixed direction vectors, whereas the new MADS algorithm uses a random selection of vectors to define the mesh.
The following options are available in the gatool and when using the ga function at the command prompt:
The new Constraints panel has a Nonlinear constraint function field in addition to fields for linear constraints and bounds for solving constrained optimization problems
New Max constraint (@gaplotmaxconstr) option in the Plot pane to plot the maximum nonlinear constraint violation at each generation
New crossover function, Arithmetic (@crossoverarithmetic), available in the Crossover panel that creates children that are the weighted arithmetic mean of two parents
New mutation function, Adaptive Feasible (mutationadaptfeasible), available in the Crossover panel that randomly generates directions that are adaptive with respect to the last successful or unsuccessful generation. This function is the default for constrained problems
New Algorithm settings panel for selecting algorithm specific parameters, such as the penalty parameters, Initial penalty and Penalty factor, for a nonlinear constraint algorithm
New Hybrid function, fmincon, for constrained problems
New Nonlinear constraint tolerance parameter in Stopping criteria
The following options are available in the psearchtool and when using the patternsearch function at the command prompt:
Constraints now has a Nonlinear constraint function option to solve for constrained optimization problems
New Max constraint (@psplotmaxconstr) option in the Plot pane to plot the maximum nonlinear constraint violation at each generation
Updated Poll method and Search method options for selecting the GPS or MADS algorithms
New Algorithm settings panel for selecting algorithm specific parameters, such as the penalty parameters, Initial penalty and Penalty factor, for a nonlinear constraint algorithm
New Time limit and Nonlinear constraint tolerance parameters in Stopping criteria
The Genetic Algorithm and Direct Search Toolbox™ contains the following new demos for Version 2.0:
Optimization of Non-smooth Objective Function
Constrained Minimization Using the Genetic Algorithm
Constrained Minimization Using the Pattern Search
Optimization of Stochastic Objective Function
Using the Genetic Algorithm and Direct Search Toolbox
| Version 2.0.1 (R2006a) Genetic Algorithm and Direct Search Toolbox™ Software | Compatibility Summary for Genetic Algorithm and Direct Search Toolbox™ Software | |
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