STUDY OF THE BEE COLONY METHOD IN OPTIMIZING PLANS OF MULTIFACTOR EXPERIMENTS

The article is devoted to the study of the effectiveness of the method of bee colonies in the context of optimization of plans of multivariate experiments. Examples of the effectiveness of the bee colony method in the optimization of multivariate experiments in comparison with other optimization methods are given. This article emphasizes the use of the bee colony method as an effective means of optimizing multivariate experimental designs. The article discusses in detail the algorithm of bee colonies, its scheme and implementation in the form of a program in the C# programming language. The authors give specific examples of the application of the algorithm in various areas, such as the eddy current converter, the study of the process of measuring the current density of galvanic baths, and the analysis of a section of a machine shop with numerical software control. The article examines the productivity of the method of bee colonies with many factors of the experiment, in particular with an increase in their number. The authors review the accuracy of the results and emphasize the importance of careful parameter selection and the need for high computer power to achieve optimal results in scientific research. This article will be a useful tool for scientists and practitioners looking for a way to improve the results of multivariate experiments in various fields of science and industry.

Authors

Publication Details

Journal
Metrology and instruments
Published
2024-12-13
DOI
https://doi.org/10.30837/2663-9564.2024.2.02
Primary Topic
Simulation Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

STUDY OF THE BEE COLONY METHOD IN OPTIMIZING PLANS OF MULTIFACTOR EXPERIMENTS

Mikola Koshovyi, Denis Kuraksin
Metrology and instruments
Simulation Techniques and Applications
article

STUDY OF THE BEE COLONY METHOD IN OPTIMIZING PLANS OF MULTIFACTOR EXPERIMENTS

Mikola Koshovyi, Denis Kuraksin
article en

Abstract

The article is devoted to the study of the effectiveness of the method of bee colonies in the context of optimization of plans of multivariate experiments. Examples of the effectiveness of the bee colony method in the optimization of multivariate experiments in comparison with other optimization methods are given. This article emphasizes the use of the bee colony method as an effective means of optimizing multivariate experimental designs. The article discusses in detail the algorithm of bee colonies, its scheme and implementation in the form of a program in the C# programming language. The authors give specific examples of the application of the algorithm in various areas, such as the eddy current converter, the study of the process of measuring the current density of galvanic baths, and the analysis of a section of a machine shop with numerical software control. The article examines the productivity of the method of bee colonies with many factors of the experiment, in particular with an increase in their number. The authors review the accuracy of the results and emphasize the importance of careful parameter selection and the need for high computer power to achieve optimal results in scientific research. This article will be a useful tool for scientists and practitioners looking for a way to improve the results of multivariate experiments in various fields of science and industry.

Metrology and instruments(2)
Industry, innovation and infrastructure
Openalex Percentile: Top 71%
Simulation Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.