A genetic algorithm tutorial
@article{Whitley1994AGA, title={A genetic algorithm tutorial}, author={L. D. Whitley}, journal={Statistics and Computing}, year={1994}, volume={4}, pages={65-85}, url={https://api.semanticscholar.org/CorpusID:3447126} }
This tutorial covers the canonical genetic algorithm as well as more experimental forms of genetic algorithms, including parallel island models and parallel cellular genetic algorithms. The tutorial…
4,267 Citations
A Genetic Programming Tutorial
- 2003
Computer Science
This chapter introduces the basics of genetic programming and touches upon some of the more advanced variants of genetic Programming as well as its theoretical foundations.
An Introduction to Genetic Algorithms and Evolution
- 2002
Computer Science, Mathematics
The history, theory and mathematical background, applications, and the current direction of both Genetic Algorithms and Evolution Strategies are examined.
Introduction to genetic algorithms
- 2007
Computer Science, Mathematics
The Introduction to Genetic Algorithms Tutorial is aimed at GECCO attendees with limited knowledge of genetic algorithms, and will start "at the beginning," describing first a "classical" genetic algorithm in terms of the biological principles on which it is loosely based, then some of the fundamental results that describe its performance, described using the schema concept.
Genetic Algorithms
- 2010
Computer Science, Business
This article provides an introduction to genetic algorithms as well as numerous pointers for obtaining additional information.
Genetic algorithms overview
- 2000
Computer Science
This paper presents genetic algorithms, adaptive methods which may be used to solve search and optimisation problems, and the basic principles of GAs, first laid down rigorously by Holland.
A New P System Based Genetic Algorithm
- 2016
Computer Science, Engineering
The new P system based genetic algorithm (PBGA), based on the parallel mechanism of P system in membrane computing, is put forward so that the performance of GA can improve.
An overview of evolutionary algorithms: practical issues and common pitfalls
- 2001
Computer Science, Engineering
Foundations of Evolutionary Algorithms
- 2018
Computer Science
Evolutionary algorithms are a broad class of stochastic adaptation algorithms inspired by biological evolution—the process that allows populations of organisms to adapt to their surrounding…
Genetic optimization algorithms applied toward mission computability models
- 2020
Computer Science, Engineering
This paper describes the genetic optimization algorithms to a mission-critical and constraints-aware computation problem.
Parallel Population Models for Genetic Algorithms
- 1996
Computer Science
A flexible parallel population model for genetic algorithms is derived, which contains all the above models as a special case and could nevertheless be implemented on many parallel architectures.
57 References
Cellular Genetic Algorithms
- 1993
Computer Science
This chapter introduces the applications of cellular automata in genetic algorithms, which makes it especially suitable for dealing with complex and nonlinear problems which are difficult to be solved by general searching methods.
Modeling Simple Genetic Algorithms
- 1995
Computer Science, Mathematics
The infinite- and finite-population models of the simple genetic algorithm are extended and unified, The result incorporates both transient and asymptotic GA behavior. This leads to an interpretation…
Genetic Algorithms in Search Optimization and Machine Learning
- 1988
Computer Science, Mathematics
This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
A Survey of Evolution Strategies
- 1991
Computer Science
Evolution Strategies are algorithms which imitate the principles of natural evolution as a method to solve parameter optimization problems and adaptation of the strategy parameters for the mutation variances as well as their covariances are described.
Genetic Algorithms for Real Parameter Optimization
- 1990
Computer Science, Mathematics
Selection in Massively Parallel Genetic Algorithms
- 1991
Computer Science, Biology
This paper characterize the difference between panmictic and local selection/mating schemes in terms of diversity of alleles, diversity of genotypes, the inbreeding, and the speed and robustness of the genetic algorithm.
Explicit Parallelism of Genetic Algorithms through Population Structures
- 1990
Computer Science
This paper specifies an algorithm which uses only local rules and local data making it massively parallel with an observed linear speedup on a transputer-based parallel system, and shows that both convergence speed and final quality are improved in comparison to a genetic algorithm without population structure.
A Comparative Analysis of Selection Schemes Used in Genetic Algorithms
- 1990
Computer Science, Mathematics
A Study of Reproduction in Generational and Steady State Genetic Algorithms
- 1990
Computer Science
A Note on Boltzmann Tournament Selection for Genetic Algorithms and Population-Oriented Simulated Annealing
- 1990
Computer Science
In this note, the motivation, the theory of operation, some proof-of-principle computational experiments, and a Pascal implementation of the algorithm are presented.