Genetic Algorithm and Direct Search Toolbox™ 2.3

Product Description

• Introduction and Key Features
• Graphical User Interface and Command-Line Functions
• Genetic Algorithm Tools
• Direct Search and Simulated Annealing Tools
• Solving Constrained Optimization Problems and Using Other Solvers
• Displaying, Monitoring, and Outputting Results

Introduction

Genetic Algorithm and Direct Search Toolbox extends the optimization capabilities in MATLAB and Optimization Toolbox with tools for using genetic algorithms, simulated annealing, and direct search. You can use these algorithms for problems that are difficult to solve with traditional optimization techniques, including problems that are not well defined or are difficult to model mathematically. You can also use them when computation of the objective function is discontinuous, highly nonlinear, stochastic, or has unreliable or undefined derivatives.

Genetic Algorithm and Direct Search Toolbox complements other optimization methods to help you find good starting points. You can then use traditional optimi­zation techniques to refine your solution.

Toolbox functions, accessible through a graphical user interface (GUI) or the MATLAB command line, are written in the open MATLAB language. This means that you can inspect the algorithms, modify the source code, and create your own custom functions.

Key Features

• Graphical user interfaces and command-line functions for quickly setting up problems, setting algorithm options, and monitoring progress
• Genetic algorithm tools with options for creating initial population, fitness scaling, parent selection, crossover, and mutation
• Direct search tools that implement a pattern search method, with options for defining mesh size, polling technique, and search method
• Simulated annealing and threshold acceptance tools that implement a random search method, with options for defining annealing process, temperature schedule, and acceptance criteria
• Ability to solve optimization problems with nonlinear, linear, and bound constraints
• Functions for integrating Optimization Toolbox and MATLAB routines with the genetic or direct search algorithm
• Support for automatic M-code generation

Genetic Algorithm and Direct Search Toolbox helps you solve problems not easily addressed by traditional optimization techniques, such as the table lookup function shown in the plot above. The toolbox GUIs help you quickly set up and solve your optimization problems. Click on image to see enlarged view.