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Everything about Population model (evolutionary algorithm)
Population models of evolutionary algorithms
The population model of an evolutionary algorithm (EA) describes the structural properties of its population to which its members are subject. A population is the set of all proposed solutions of an EA considered in one iteration, which are also called individuals according to the biological role model. The individuals of a population can generate further individuals as offspring with the help of the genetic operators of the procedure. Wikipedia →
🧠Start here: a 6-step reading path
- Read the overview: Population model (evolutionary algorithm)A 5-minute orientation
- Skim a recent paper: Enhanced goal direction and remodeling of population distributions multimodal multi-objective evolutionary algorithmInfluential work since 2022
- Pick up a classic book: Simulation-Based Algorithms for Markov Decision ProcessesThe most-reprinted book on the subject
- Read the landmark paper: Rigorous Analysis of Multi-Factorial Evolutionary Algorithm as Multi-Population Evolution ModelCited 20 times
- Go sideways: Evolutionary algorithmA closely related topic
- Go sideways: Premature convergenceA closely related topic
đź“– Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Rigorous Analysis of Multi-Factorial Evolutionary Algorithm as Multi-Population Evolution Model
An Evolutionary Search Algorithm for Covariate Models in Population Pharmacokinetic Analysis
An Adaptive Genetic Algorithm Based on Multi-Population Parallel Evolutionary for Highway Alignment Optimization Model
Study on Diversity of Population in Game model based Co-evolutionary Algorithm for Multiobjective optimization
🆕 Influential since 2022
đź“š Books worth reading
Simulation-Based Algorithms for Markov Decision ProcessesHyeong Soo Chang · 2010
Evolutionary Computation, Machine Learning and Data Mining in BioinformaticsLeonardo Vanneschi · 2012
Neuro-fuzzy and soft computingJyh-Shing Roger Jang, Chuen-Tsai Sun · 1996
SmartDataInman Harvey · 2013
Principles of gene manipulation and genomicsS. B. Primrose · 2006
Foundations of genetic algorithms 7Kenneth A. De Jong, Riccardo Poli · 2001
Applications of Evolutionary ComputationAnna Isabel Esparcia-Alcázar · 2013- 📕FOGA '09Workshop on Foundations of Genetic Algorithms (10th 2009 Orlando, Fla.) · 2009
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
đź”— Related topics
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