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

Ranks01:02

Ranks

Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
Sieve Analysis and Grading Curves01:19

Sieve Analysis and Grading Curves

Sieve analysis is a method used to determine the particle size distribution of aggregate materials. This process involves the following steps:
Graphical Representation of Inequalities01:28

Graphical Representation of Inequalities

The graph of the equation where y equals x squared forms a curve known as a parabola. This curve acts as a boundary in the coordinate plane, dividing it into distinct regions based on the relative position of points.When the equality sign in the equation is replaced with an inequality—such as greater than, less than, greater than or equal to, or less than or equal to—the graphical representation changes from a single curve into a broader shaded area that signifies the set of all points...
Incomplete Dominance01:43

Incomplete Dominance

Gregor Mendel's work (1822 - 1884) was primarily focused on pea plants. Through his initial experiments, he determined that every gene in a diploid cell has two variants called alleles inherited from each parent. He suggested that amongst these two alleles, one allele is dominant in character and the other recessive. The combination of alleles determines the phenotype of a gene in an organism.
Application of Nonlinear Inequalities01:29

Application of Nonlinear Inequalities

A nonlinear inequality describes a comparison involving an expression that curves or behaves more complexly than a straight line. These inequalities often appear in forms that include squares, products, or variables in the denominator.To solve such an inequality, one starts by rewriting it so that zero appears on one side. For example, the inequality:  can be factored as: This form makes it easier to identify the values that cause the expression to equal zero. In this case, the key values are 3...
Deductive Reasoning01:16

Deductive Reasoning

Deductive reasoning, or deduction, is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction from inductive reasoning. It uses a general principle or law to predict specific results. From these general principles, a scientist can predict specific results that remain valid as long as the general principles are correct.For example, a researcher can make specific predictions from the hypothesis "butterflies are attracted...

You might also read

Related Articles

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

Sort by
Same author

A novel machine learning application: Water quality resilience prediction Model.

The Science of the total environment·2021
Same author

Towards urban resilience through Sustainable Drainage Systems: A multi-objective optimisation problem.

Journal of environmental management·2020
Same author

A Hidden Markov Model Approach to the Problem of Heuristic Selection in Hyper-Heuristics with a Case Study in High School Timetabling Problems.

Evolutionary computation·2016
Same author

Ant colony optimisation of decision tree and contingency table models for the discovery of gene-gene interactions.

IET systems biology·2015
Same author

Gene expression rule discovery and multi-objective ROC analysis using a neural-genetic hybrid.

International journal of data mining and bioinformatics·2013
Same author

Metabolic tinker: an online tool for guiding the design of synthetic metabolic pathways.

Nucleic acids research·2013
Same journal

Computing Optimal Populations for Binary Problems using Logic Minimization.

Evolutionary computation·2026
Same journal

Enhancing Generalization and Scalability for Multi-Objective Optimization with Population Pre-Training.

Evolutionary computation·2026
Same journal

XCS for Sequential Perceptual Aliasing in Multi-Step Decision Making.

Evolutionary computation·2026
Same journal

A dynamic multi-objective evolutionary algorithm using dual-space prediction and surrogate-based sampling.

Evolutionary computation·2026
Same journal

Adapting MOEA/D to CMA-ES for Dealing with Ill-conditioned Multiobjective Problems.

Evolutionary computation·2026
Same journal

Editorial of the Special Issue: Parallel Problem Solving from Nature PPSN 2024 Extended Versions of Best Paper Candidates.

Evolutionary computation·2026
See all related articles

Related Experiment Video

Updated: Jun 1, 2026

A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'
10:31

A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'

Published on: February 10, 2017

Deductive sort and climbing sort: new methods for non-dominated sorting.

Kent McClymont1, Ed Keedwell

  • 1College of Engineering, Mathematics and Physical Sciences, University of Exeter, EX4 4QJ, UK. km314@exeter.ac.uk

Evolutionary Computation
|May 20, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces two novel non-dominated sorting methods, deductive sort and climbing sort, for evolutionary algorithms. These methods improve computational efficiency in multi-objective optimization problems.

More Related Videos

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Related Experiment Videos

Last Updated: Jun 1, 2026

A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'
10:31

A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'

Published on: February 10, 2017

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Area of Science:

  • Computational intelligence
  • Optimization algorithms
  • Evolutionary computation

Background:

  • Many real-world problems involve multi-objective optimization.
  • Evolutionary algorithms often use non-dominance for solution selection.
  • Current non-dominated sorting methods can be computationally expensive for large datasets.

Purpose of the Study:

  • To present two novel methods for non-dominated sorting: deductive sort and climbing sort.
  • To evaluate the efficiency of these new methods compared to existing algorithms.

Main Methods:

  • Developed deductive sort and climbing sort algorithms.
  • Compared performance against NSGA-II's fast non-dominated sort and omni-optimizer's non-dominated rank sort.
  • Analyzed computational complexity and number of comparisons.

Main Results:

  • Deductive sort and climbing sort demonstrate improved computational efficiency.
  • Reductions in comparisons were observed by utilizing inferred dominance relationships.
  • The new methods offer a more efficient approach to sorting in multi-objective optimization.

Conclusions:

  • The proposed deductive and climbing sorts are efficient alternatives for non-dominated sorting.
  • These methods can significantly reduce computational cost in evolutionary multi-objective optimization.
  • Inferred dominance relationships offer a promising avenue for algorithmic improvement.