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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

438
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...
438
Methods of Medium Optimization01:28

Methods of Medium Optimization

69
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
69
Trial and Error and Algorithm01:12

Trial and Error and Algorithm

544
A problem-solving strategy is a plan of action used to find a solution. Different strategies have distinct action plans. Trial and error involves trying different solutions until one works. For instance, to fix a broken printer, you might check ink levels, ensure the paper tray isn't jammed, and verify the printer's connection to your laptop. This method can be time-consuming but is commonly used. Thomas Edison, for example, used trial and error to find a suitable filament for the light...
544
Optimization Problems01:26

Optimization Problems

216
Optimization problems often involve identifying maximum or minimum values under specific constraints. A well-known example is determining the longest horizontal pipe that can be moved around a right-angled corner, where a 3-meter-wide hallway meets a 2-meter-wide hallway. This scenario, common in architectural design and industrial transport, can be understood conceptually through geometric and trigonometric reasoning.To visualize the problem, consider the pipe as a straight line that touches...
216
Genetic Screens02:46

Genetic Screens

4.6K
Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
4.6K
What is Genetic Engineering?00:49

What is Genetic Engineering?

70.4K
Overview
70.4K

You might also read

Related Articles

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

Sort by
Same author

Global Analysis the Potential Medicinal Substances of Shuangxia Decoction and the Process <i>In Vivo</i> via Mass Spectrometry Technology.

Frontiers in pharmacology·2021
Same author

Relationship Between Rheumatoid Arthritis and Pulmonary Function Measures on Spirometry in the UK Biobank.

Arthritis & rheumatology (Hoboken, N.J.)·2021
Same author

Incorporating Guanidinium as Perovskitizer-Cation of Two-Dimensional Metal Halide for Crystal-Array Photodetectors.

Chemistry, an Asian journal·2021
Same author

Guided suturing technique for midface lift through minimal temporal incision.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS·2021
Same author

Drug-induced liver injury: Oltipraz and C2-ceramide intervene HNF-1α/GSTA1 expression via JNK signaling pathway.

Journal of applied toxicology : JAT·2021
Same author

Regulation of MRP4 Expression by circHIPK3 via Sponging miR-124-3p/miR-4524-5p in Hepatocellular Carcinoma.

Biomedicines·2021
Same journal

Multiphysics Investigation on Thermal Characteristics of Internal Bio-Inspired V-Ribbed Cooling Channels for Outer Rotor PMSM.

Biomimetics (Basel, Switzerland)·2026
Same journal

Smart Logistics Model for Supply Chain Management via Brain-Inspired Geometric Deep Networks.

Biomimetics (Basel, Switzerland)·2026
Same journal

A Systematic Taxonomy of the Sunflower Optimization Algorithm: Variants, Hybridization Strategies, Applications, and Research Directions.

Biomimetics (Basel, Switzerland)·2026
Same journal

Toward a Compositional Theory of Trust in Embodied Intelligence: A QNLP Framework for Modeling Context, Interaction, and Trustworthiness.

Biomimetics (Basel, Switzerland)·2026
Same journal

Empirical Logic for Bio-Inspired Soft Computing: Illustrative Applications in Control Engineering and Cluster Analysis.

Biomimetics (Basel, Switzerland)·2026
Same journal

A Modified Multi-Strategy Dhole Optimization Algorithm and Its Engineering Applications.

Biomimetics (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Apr 28, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.0K

An Improved Genghis Khan Shark Optimization Algorithm for Solving Optimization Problems.

Yanjiao Wang1, Jiaqi Wang1

  • 1School of Electrical Engineering, Northeast Electric Power University, 169 Changchun Road, Jilin 132012, China.

Biomimetics (Basel, Switzerland)
|April 27, 2026
PubMed
Summary
This summary is machine-generated.

The improved Genghis Khan Shark Optimization (IGKSO) algorithm enhances metaheuristic performance by addressing local optima and improving convergence speed and accuracy. This novel approach boosts optimization efficiency for complex problems.

Keywords:
Genghis Khan shark optimizernovel diversity assessment mechanismopposition-based learningparameter adaptation strategypopulation partitioning method

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

12.6K
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

16.2K

Related Experiment Videos

Last Updated: Apr 28, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.0K
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

12.6K
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

16.2K

Area of Science:

  • Computational Intelligence
  • Optimization Algorithms
  • Metaheuristic Computing

Background:

  • The Genghis Khan Shark Optimization (GKSO) algorithm, while innovative, suffers from local optima convergence and suboptimal speed and accuracy.
  • Addressing these limitations is crucial for advancing metaheuristic algorithm performance in complex problem-solving.

Purpose of the Study:

  • To introduce an improved Genghis Khan Shark Optimization (IGKSO) algorithm designed to overcome the inherent limitations of the original GKSO.
  • To enhance convergence speed, accuracy, and robustness against local optima in metaheuristic optimization.

Main Methods:

  • Implemented a population partitioning strategy based on cosine similarity and fitness to differentiate between disadvantaged (foraging) and advantaged (moving) populations.
  • Introduced an adaptive step-size mechanism and subspace method to prevent boundary overflow and maintain population diversity during foraging.
  • Incorporated opposition-based learning in the hunting stage and a diversity assessment criterion in the self-protection phase to prevent suboptimal convergence and real-time diversity supplementation.

Main Results:

  • The IGKSO algorithm demonstrated significant improvements over the standard GKSO and eight other high-performance algorithms.
  • Evaluations on the CEC2017 and CEC2019 benchmark test sets confirmed IGKSO's superior convergence speed and accuracy.
  • The proposed enhancements effectively mitigated the tendency towards local optima and improved overall optimization performance.

Conclusions:

  • The IGKSO algorithm represents a substantial advancement in metaheuristic optimization, offering enhanced efficiency and reliability.
  • The strategic population partitioning, adaptive mechanisms, and opposition-based learning contribute to superior performance in complex optimization tasks.
  • IGKSO provides a more effective and robust alternative for researchers and practitioners seeking advanced optimization solutions.