gatbxa1 - 1 Tutorial MATLAB has a wide variety of functions...

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Genetic Algorithm Toolbox User’s Guide 1-1 1 Tutorial MATLAB has a wide variety of functions useful to the genetic algorithm practitioner and those wishing to experiment with the genetic algorithm for the f rst time. Given the versatility of MATLAB’s high-level language, problems can be coded in m- f les in a fraction of the time that it would take to create C or Fortran programs for the same purpose. Couple this with MATLAB’s advanced data analysis, visualisation tools and special purpose application domain toolboxes and the user is presented with a uniform environment with which to explore the potential of genetic algorithms. The Genetic Algorithm Toolbox uses MATLAB matrix functions to build a set of versatile tools for implementing a wide range of genetic algorithm methods. The Genetic Algorithm Toolbox is a collection of routines, written mostly in m- f les, which implement the most important functions in genetic algorithms.
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Genetic Algorithm Toolbox User’s Guide 1-2 Installation Instructions for installing the Genetic Algorithm Toolbox can be found in the MATLAB installation instructions. It is recommended that the f les for this toolbox are stored in a directory named genetic off the main matlab/toolbox directory. A number of demonstrations are available. A single-population binary-coded genetic algorithm to solve a numerical optimization problem is implemented in the m- f le sga.m . The demonstration m- f le mpga.m implements a real-valued multi- population genetic algorithm to solve a dynamic control problem. Both of these demonstration m- f les are discussed in detail in the Examples Section. Additionally, a set of test functions, drawn from the genetic algorithm literature, are supplied in a separate directory, test_fns , from the Genetic Algorithm Toolbox functions. A brief description of these test functions is given at the end of the Examples Section. A further document describes the implementation and use of these functions.
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Genetic Algorithm Toolbox User’s Guide 1-3 An Overview of Genetic Algorithms In this Section we give a tutorial introduction to the basic Genetic Algorithm (GA) and outline the procedures for solving problems using the GA. What are Genetic Algorithms? The GA is a stochastic global search method that mimics the metaphor of natural biological evolution. GAs operate on a population of potential solutions applying the principle of survival of the f ttest to produce (hopefully) better and better approximations to a solution. At each generation, a new set of approximations is created by the process of selecting individuals according to their level of f tness in the problem domain and breeding them together using operators borrowed from natural genetics. This process leads to the evolution of populations of individuals that are better suited to their environment than the individuals that they were created from, just as in natural adaptation.
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This note was uploaded on 05/01/2011 for the course ELECTRICAL EE5602 taught by Professor Xuequan during the Spring '11 term at City University of Hong Kong.

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gatbxa1 - 1 Tutorial MATLAB has a wide variety of functions...

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