Diversity-Guided Evolutionary Algorithms
By R. K. Ursem. Parallel Problem Solving from Nature, 2002
368 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Theory and Mathematics
View Paper: https://www.semanticscholar.org/paper/4d7444114f23516a4ec697423c0aaafb2644f337
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Leandro dos S. Coelho
- Shahryar Rahnamayan
- Hui Wang
- Jeng‐Shyang Pan
- Graham Kendall
- Hui Sun
- Edmund Kieran Burke
- Changhe Li
In Computational Theory and Mathematics
- Leandro dos S. Coelho
- Shahryar Rahnamayan
- Hui Wang
- Edmund Kieran Burke
- Changhe Li
- Renato Antonio Krohling
- Seyedali Mirjalili
- Konstantinos E. Parsopoulos
Citations in the corpus
- Diversity enhanced particle swarm optimization with neighborhood search (2013, background): “Recently, Ursem [51] proposed a diversity-guided evolutionary algorithm, which uses a diversity measure to alternate between exploring and exploiting behaviors.”
- Diversity in genetic programming: an analysis of measures and correlation with fitness (2004, background): “Ursem [52] cited the importance of high and low diversity phases in an evolutionary strategy framework.”
- Coevolutionary Particle Swarm Optimization Using Gaussian Distribution for Solving Constrained Optimization Problems (2006, methodology): “An approach using a diversity of the population borrowed from EA has been proposed by Ursem [28].”