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Genetic Algorithms in Search Optimization and Machine Learning
- D. Goldberg
- Computer Science
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 niched Pareto genetic algorithm for multiobjective optimization
- Jeffrey D. Horn, Nicholas Nafpliotis, D. Goldberg
- Computer ScienceProceedings of the First IEEE Conference on…
- 27 June 1994
The Niched Pareto GA is introduced as an algorithm for finding the Pare to optimal set and its ability to find and maintain a diverse "Pareto optimal population" on two artificial problems and an open problem in hydrosystems is demonstrated.
BOA: the Bayesian optimization algorithm
Preliminary experiments show that the BOA outperforms the simple genetic algorithm even on decomposable functions with tight building blocks as a problem size grows.
A Comparative Analysis of Selection Schemes Used in Genetic Algorithms
Genetic Algorithms with Sharing for Multimodalfunction Optimization
The compact genetic algorithm
- G. Harik, F. Lobo, D. Goldberg
- Computer ScienceIEEE International Conference on Evolutionary…
- 4 May 1998
The cGA represents the population as a probability distribution over the set of solutions, and is operationally equivalent to the order-one behavior of the simple GA with uniform crossover.
Genetic Algorithms and Machine Learning
There is no a priori reason why machine learning must borrow from nature, but many machine learning systems now borrow heavily from current thinking in cognitive science, and rekindled interest in neural networks and connectionism is evidence of serious mechanistic and philosophical currents running through the field.
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
- D. Goldberg
From the Publisher: The Design of Innovation illustrates how to design and implement competent genetic algorithms - genetic algorithms that solve hard problems quickly, reliably, and accurately -…
An Investigation of Niche and Species Formation in Genetic Function Optimization
This contribution briefly describes problems preventing niche formation in conventional genetic algorithms, a crowding method for niche formation and analysis of results when optimizing two multimodal functions.