## Practical Genetic AlgorithmsThis book deals with the fundamentals of genetic algorithms and their applications in a variety of different areas of engineering and science Most significant update to the second edition is the MATLAB codes that accompany the text Provides a thorough discussion of hybrid genetic algorithms Features more examples than first edition Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file. |

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A dificulty with optimization is determining if a given minimum is the best (global) minimum or a suboptimal one (local).

Finding the min. of a nonlinear fct. is especially difficult. Typical approaches to highly nonlinear problems involve either linearizing the problem in a very confined region or restricting the opimization to a small region. In short, we cheat.

#### Review: Practical Genetic Algorithms [With CDROM]

User Review - Atheer - GoodreadsUseful book with easy to digest approach to GA. helped me to understand the GA toolbox in Matlab Read full review

### Contents

1 | |

2 The Binary Genetic Algorithm | 27 |

3 The Continuous Genetic Algorithm | 51 |

4 Basic Applications | 67 |

5 An Added Level of Sophistication | 95 |

6 Advanced Applications | 151 |

7 More Natural Optimization Algorithms | 187 |

### Common terms and phrases

allele antenna approach array average Bäck binary Chapter chromosome combinations Conf convergence cost function cost surface crossover crossover point Ellen Haupt encoding epistasis equation Evol evolution evolution strategy evolutionary algorithms example find the minimum fitness gene Genetic Algorithms Genetic Programming global minimum Goldberg Gray code Hessian matrix horse implementation initial population integer linear mainbeam master–slave mating MATLAB matrix method Michalewicz minimization minimum cost Morgan Kaufmann mutation rate natural selection Nelder-Mead Nkeep nonlinear Npop number of bits number of function Nvar offspring optimization algorithms optimum pair parallel parents Pareto front particle particle swarm optimization path performance pheromone plot possible Practical Genetic Algorithms quantization radar cross section randomly rank rithm robot sampling schema shown in Figure sidelobe simplex simulated annealing solution solve space speedup strategy subroutine Table tion tournament selection traveling salesperson problem uniform crossover variable values vector weighting