| Version 2.2 (R2007b) Genetic Algorithm and Direct Search Toolbox™ Software Release Notes | ![]() |
This table summarizes what's new in version 2.2 (R2007b):
| 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 described here:
Multiobjective Optimization with Genetic Algorithm and Custom Data Types
Hybrid Multiobjective Optimization Combining Genetic Algorithm with Optimization Toolbox
Multiobjective optimization, with linear and bound constraints, is now available through the new function gamultiobj. This function determines optimal Pareto fronts from specified criteria, including Pareto fronts that are nonconvex, disconnected, or both.
Optimization Toolbox also contains multiobjective functionality, but cannot reliably generate optimal Pareto fronts if these are nonconvex or disconnected.
Two new demos illustrate this feature. See New Demos following.
The new function gamultiobj also supports multiobjective optimization with custom data types, including binary.
To determine multiobjective optimizations more accurately, you can now combine the new function gamultiobj with the existing function fgoalattain from Optimization Toolbox.
The functions ga and patternsearch now accept vectorized function inputs with nonlinear constraints. The new function gamultiobj does as well.
Two accompanying demos illustrate the use of the new multiobjective genetic algorithm function gamultiobj:
gamultiobjfitness uses gamultiobj to solve a simple problem with one decision variable and two objectives.
gamultiobjoptionsdemo shows how to set options for multiobjective optimization with a simple genetic algorithm problem.
![]() | Version 2.3 (R2008a) Genetic Algorithm and Direct Search Toolbox Software | Version 2.1 (R2007a) Genetic Algorithm and Direct Search Toolbox Software | ![]() |
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