## An Executable Model of a Simple Genetic Algorithm (1992)

Venue: | Foundations of Genetic Algorithms 2 |

Citations: | 55 - 5 self |

### BibTeX

@INPROCEEDINGS{Whitley92anexecutable,

author = {Darrell Whitley},

title = {An Executable Model of a Simple Genetic Algorithm},

booktitle = {Foundations of Genetic Algorithms 2},

year = {1992},

pages = {45--62},

publisher = {Morgan Kaufmann}

}

### OpenURL

### Abstract

A set of executable equations are defined which model the ideal behavior of a simple genetic algorithm. The equations assume an infinitely large population and require the enumeration of all points in the search space.

### Citations

7728 |
Genetic Algorithms
- Goldberg
(Show Context)
Citation Context ...oblem. P(Z,t + l) = (1- Pc)P(Z,t)T + Pc { P(Z,t)T(1-1osses)-f gains. } which reduces to P(Z,t-fl) -- P(Z,t)f(;)(1-{Pc losses})-f{Pc gains.} This is an idealized version of a simple genetic algorithm (=-=Goldberg, 1989-=-a). In the current formulation, Z might refer to either a string or a schema representing a hyperplane. P(Z,t) is the proportion of the population that samples the string (schema) Z at time t. The exp... |

197 |
Modeling genetic algorithms with Markov chains
- Nix, Vose
- 1992
(Show Context)
Citation Context ...as preliminary work using these equations to study parallel island model genetic algorithms. More complex extension of the Vose and Liepins model include finite population models using Markov Models (=-=Nix and Vose, 1992-=-). Vose (1992) surveys the current state of this research. 4 Implementation Complexity and Preliminary Results A computer program has been written which requires access to a copy of an evaluation func... |

156 |
Genetic algorithms and Walsh functions: Part I, a gentle introduction
- Goldberg
- 1989
(Show Context)
Citation Context ...oblem. P(Z,t + l) = (1- Pc)P(Z,t)T + Pc { P(Z,t)T(1-1osses)-f gains. } which reduces to P(Z,t-fl) -- P(Z,t)f(;)(1-{Pc losses})-f{Pc gains.} This is an idealized version of a simple genetic algorithm (=-=Goldberg, 1989-=-a). In the current formulation, Z might refer to either a string or a schema representing a hyperplane. P(Z,t) is the proportion of the population that samples the string (schema) Z at time t. The exp... |

126 | Simple genetic algorithms and the minimal deceptive problem - Goldberg - 1987 |

97 | Fundamental principles of deception in genetic search
- Whitley
- 1991
(Show Context)
Citation Context ...length of critical schemata will appear to be shorter than they actually are. Figure 1 illustrate the execution of these equations on an embedded 3 bit fully deceptive problem (c.f., Goldberg, 1989b; =-=Whitley, 1991-=-) as well as the results of executing an actual simple genetic algorithm using a population size of 625. The three bits corresponding to the deceptive function are located at positions 1, 5 and 9; the... |

26 | An analysis of reproduction and crossover in a binary-coded genetic algorithm - Bridges, Goldberg - 1987 |

16 |
Representation Issues in Genetic Algorithms
- Liepins, Vose
- 1990
(Show Context)
Citation Context ...ponding strings for computing the formula for any and all terms of the form P(Z,t+i). The translation is accomplished using bitwise addition modulo 2 (i.e., a bitwise exclusive-or denoted by ) (c.f., =-=Liepins and Vose, 1990-=-). The equations already presented are applicable to 3 bit problems corresponding to either schemata or strings of 3 bits; of course, if schemata are modeled (as opposed to complete strings) the equat... |

10 |
Deception, Dominance and Implicit Parallelism in Genetic Search
- Whitley
- 1992
(Show Context)
Citation Context ...ains occur when new schema samples are generated by recombination of strings that do not contain copies of the schema h. The following equations have recently been used to study 3 and 4 bit problems (=-=Whitley, 1992-=-). These equations are based on similar equations for 2 bit problems used by Goldberg (1987) to study the minimally deceptive problem. P(Z,t + l) = (1- Pc)P(Z,t)T + Pc { P(Z,t)T(1-1osses)-f gains. } w... |

8 | Some effects of selection procedures on hyperplane sampling by genetic algorithms - Schaffer - 1987 |

1 | Modeling Simple Genetic Algorithms. Foundations of Genetic Algorithms-2 - Vase - 1992 |