• Corpus ID: 3547258

Population Structures C 6 . 2 Speciation methods

  title={Population Structures C 6 . 2 Speciation methods},
  author={Kalyanmoy Deb and William M. Spears},
In nature, a species is defined as a collection of phenotypically similar individuals. Many biologists believe that individuals in a sexually reproductive species can be created and maintained by allowing restrictive mating only among individuals from the same species. The connection between the formation of multiple species in nature and in search and optimization problems lies in solving multimodal problems, where the objective is not only to find one optimal solution, but to find a number of… 

Evocube: a Genetic Labeling Framework for Polycube-Maps

This work addresses the labeling problem, which aims to precompute polycube alignment by assigning one of the base axes to each boundary face on the input by embedding labeling operations in an evolutionary heuristic, definingness, crossover, and mutations in the context of labeling optimization.

EVADING: An Evolutionary Algorithm with Dynamic Niching for Data Classification

This work proposes an evolutionary algorithm (EVADING) capable of discovering a set of accurate and diverse classification rules and uses a dynamic clustering technique as a parallel niching method to maintain rule population diversity and converge to the optimal rules for the attribute-space defined by the target dataset.



Experimental Study of Speciation in Ecological Niche Theory Using Genetic Algorithms

A case can be made for the selection of incidental phenotypic properties as a means of providing non-uniform mate selection to the point of eventually giving rise to distinct species.

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.

Genetic algorithms with dynamic niche sharing for multimodal function optimization

Dynamic niche sharing is developed that is able to efficiently identify and search multiple niches (peaks) in a multimodal domain and perform better than two other methods for multiple optima identification, standard sharing and deterministic crowding.

Massive Multimodality, Deception, and Genetic Algorithms

This paper considers the use of genetic algorithms GAs for the solution of problems that are both average sense misleading deceptive and massively multimodal and suggests a number of avenues for generalizing the notion of deception.

Intelligent behavior as an adaptation to the task environment ; Part II.

This dissertation argues that examining more closely the way animate systems cope with real-world environments can provide valuable insights about the structural requirements for intelligent behavior.

1989Genetic Algorithms in Multimodal Function Optimization

  • 1989

Genetic Algorithms in Multimodal Function Optimization Master's Thesis

  • TCGA Report
  • 1989

Intelligent Behavior as an Adaptation to the Task Environment Doctoral Dissertation

  • Dissertation Abstracts Int
  • 1982

Artificial Genetic Adaptation in Computer Control Systems Doctoral Dissertation

  • Dissertation Abstracts Int
  • 1971