Version 2.2 (R2007b) Genetic Algorithm and Direct Search Toolbox Software

This table summarizes what's new in version 2.2 (R2007b):

New Features and ChangesVersion Compatibility ConsiderationsFixed Bugs and Known ProblemsRelated Documentation at Web Site

Yes
Details below

No

Bug Reports
Includes fixes
None

New features and changes introduced in this version are described here:

Multiobjective Optimization with Genetic Algorithm

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.

Multiobjective Optimization with Genetic Algorithm and Custom Data Types

The new function gamultiobj also supports multiobjective optimization with custom data types, including binary.

Hybrid Multiobjective Optimization Combining Genetic Algorithm with Optimization Toolbox

To determine multiobjective optimizations more accurately, you can now combine the new function gamultiobj with the existing function fgoalattain from Optimization Toolbox.

Vectorized Function Inputs with Nonlinear Constraints

The functions ga and patternsearch now accept vectorized function inputs with nonlinear constraints. The new function gamultiobj does as well.

New Demos

Two accompanying demos illustrate the use of the new multiobjective genetic algorithm function gamultiobj:

  


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