Practical Genetic Algorithms

@inproceedings{Haupt1998PracticalGA,
  title={Practical Genetic Algorithms},
  author={Randy L. Haupt and Sue Ellen Haupt},
  year={1998}
}
Introduction to Optimization The Binary Genetic Algorithm The Continuous Parameter Genetic Algorithm Applications An Added Level of Sophistication Advanced Applications Evolutionary Trends Appendix Glossary Index. 
Evolutionary Computation and Metaheuristics
This chapter describes how to use metaheuristic search and evolutionary algorithms to generate covering arrays for combinatorial testing. They include, among others, genetic algorithms, simulated
Self-configuring genetic programming algorithm with modified uniform crossover
For genetic programming algorithms new variants of uniform crossover operators that introduce selective pressure on the recombination stage are proposed. Operators probabilistic rates based approach
Self-configuring Genetic Algorithm with Modified Uniform Crossover Operator
For genetic algorithms, new variants of the uniform crossover operator that introduce selective pressure on the recombination stage are proposed. Operator probabilistic rates based approach to
Optimizing complex systems
  • S. Haupt, R. Haupt
  • Computer Science
    1998 IEEE Aerospace Conference Proceedings (Cat. No.98TH8339)
  • 1998
TLDR
This paper presents two interesting applications using the genetic algorithm, the first optimizes a function that has a subjective output: music, and the second uses continuous parameters rather than the traditional binary parameters to find solutions to a nonlinear partial differential equation.
Using genetic algorithms in software optimization
TLDR
Genetic algorithms are proposed for multi-criteria optimization for very complex software applications and their effects are compared with classic algorithm effects for the same lot of applications.
Truss Optimization Using Genetic Algorithms
TLDR
The design of a program that uses genetic algorithms to optimize a truss structure, along with an example of truss optimization, are presented.
Application of genetic algorithms to construction scheduling with or without resource constraints
The difficulties encountered in scheduling construction projects with resource constraints are highlighted by means of a simplified bridge construction problem. A genetic algorithm applicable to pr...
A Hybrid Fuzzy Simplex Genetic Algorithm
This paper presents a novel hybrid genetic algorithm that has the ability of the genetic algorithms to avoid being trapped at local minimum while accelerating the speed of local search by using the
DNA coding in evolutionary computation
TLDR
This work compares two coding methods for the genetic algorithm and the effect of the developed coding methods on the algorithms is analyzed by application to classification problem.
Extended genetic algorithm: application to x-ray analysis
TLDR
New genetic operators implemented in this paper are shown to increase the convergence speed and reliability of the optimization process and are compared with the effectiveness of various optimization methods.
...
...

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