Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Life Histories01:29

Life Histories

17.9K
Overview
17.9K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

54
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
54
Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

430
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
430
Genetic Drift03:33

Genetic Drift

39.8K
Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.
39.8K
Limits to Natural Selection01:38

Limits to Natural Selection

31.3K
Organisms that are well-adapted to their environment are more likely to survive and reproduce. However, natural selection does not lead to perfectly adapted organisms. Several factors constrain natural selection.
31.3K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

41
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
41

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Convergence Properties of the (<i>μ</i>/<i>μ<sub>I</sub></i>, <i>λ</i>)-ES on the Rastrigin Function.

Proceedings of the ... ACM SIGEVO Conference on Foundations of Genetic Algorithms. Workshop on Foundations of Genetic Algorithms·2024
Same author

Progress Rate Analysis of Evolution Strategies on the Rastrigin Function: First Results.

Parallel problem solving from nature : ... PPSN ... proceedings. International Conference on Parallel Problem Solving from Nature·2024
Same author

Progress analysis of a multi-recombinative evolution strategy on the highly multimodal Rastrigin function.

Theoretical computer science·2024
Same author

Errata: Convergence Analysis of Evolutionary Algorithms That Are Based on the Paradigm of Information Geometry.

Evolutionary computation·2020
Same author

Analysis of the <math><mrow><mo>(</mo><mi>μ</mi><mo>/</mo><msub><mi>μ</mi><mi>I</mi></msub><mo>,</mo><mi>λ</mi><mo>)</mo></mrow></math>-CSA-ES with Repair by Projection Applied to a Conically Constrained Problem.

Evolutionary computation·2019
Same author

The Dynamics of Cumulative Step Size Adaptation on the Ellipsoid Model.

Evolutionary computation·2014
Same journal

Semantic variation operators for multidimensional genetic programming.

Genetic and Evolutionary Computation Conference : [proceedings]. Genetic and Evolutionary Computation Conference·2022
Same journal

Toward inverse generative social science using multi-objective genetic programming.

Genetic and Evolutionary Computation Conference : [proceedings]. Genetic and Evolutionary Computation Conference·2020
Same journal

GA-Based Selection of Vaginal Microbiome Features Associated with Bacterial Vaginosis.

Genetic and Evolutionary Computation Conference : [proceedings]. Genetic and Evolutionary Computation Conference·2014
Same journal

Mask Functions for the Symbolic Modeling of Epistasis Using Genetic Programming.

Genetic and Evolutionary Computation Conference : [proceedings]. Genetic and Evolutionary Computation Conference·2012
Same journal

A Balanced Accuracy Fitness Function Leads to Robust Analysis using Grammatical Evolution Neural Networks in the Case of Class Imbalance.

Genetic and Evolutionary Computation Conference : [proceedings]. Genetic and Evolutionary Computation Conference·2011
Same journal

Alternative Cross-Over Strategies and Selection Techniques for Grammatical Evolution Optimized Neural Networks.

Genetic and Evolutionary Computation Conference : [proceedings]. Genetic and Evolutionary Computation Conference·2011
See all related articles

Related Experiment Video

Updated: Jul 2, 2025

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

8.7K

On a Population Sizing Model for Evolution Strategies Optimizing the Highly Multimodal Rastrigin Function.

Lisa Schönenberger1, Hans-Georg Beyer1

  • 1Vorarlberg University of Applied Sciences, Research Center Business Informatics, 6850 Dornbirn, Austria.

Genetic and Evolutionary Computation Conference : [Proceedings]. Genetic and Evolutionary Computation Conference
|February 19, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a model to calculate the success probability of Evolution Strategies converging to the Rastrigin function's global optimum. A population size formula is derived for reliable convergence based on search space dimensions.

Keywords:
Evolution StrategiesMathematics of computing→Bio-inspired optimizationTheory of computation→Random search heuristicsglobal convergenceglobal optimizationmulti-modal objective functionpopulation sizing

More Related Videos

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.0K
Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.1K

Related Experiment Videos

Last Updated: Jul 2, 2025

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

8.7K
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.0K
Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.1K

Area of Science:

  • Optimization algorithms
  • Computational intelligence
  • Machine learning

Background:

  • Evolution Strategies (ES) are stochastic optimization algorithms.
  • The Rastrigin function is a common benchmark for evaluating global optimization performance.
  • Determining appropriate population sizes for ES is crucial for reliable convergence.

Purpose of the Study:

  • To develop a predictive model for the convergence success probability of a vanilla Evolution Strategy on the Rastrigin function.
  • To derive a population size scaling formula for ensuring high convergence security.
  • To analyze the impact of search space dimensionality on ES performance.

Main Methods:

  • A mathematical model was developed to analyze the convergence probability of Evolution Strategies.
  • The model specifically targets the Rastrigin test function.
  • Population size scaling was investigated in relation to search space dimensionality.

Main Results:

  • A method for calculating the success probability of ES convergence to the Rastrigin global optimum was established.
  • A population size scaling formula was derived.
  • The formula enables estimation of required population sizes for guaranteed convergence security.

Conclusions:

  • The presented model provides a theoretical basis for understanding ES convergence on challenging multimodal functions.
  • The derived population size formula is a practical tool for practitioners to set appropriate population sizes.
  • This work contributes to the reliable application of Evolution Strategies in high-dimensional optimization problems.