NDLI: Orthogonal Optimization Algorithm of Swarm Intelligence Based on the Analysis of Variance Ratio

Content Provider	IEEE Xplore Digital Library
Author	Yongxian Li Jiazhong Li
Copyright Year	2009
Abstract	This paper presents an algorithm of population-based orthogonal intelligent optimization against the deficiency such as much calculation amount and slow speed of global convergence in current algorithms of swarm intelligent optimization. In view of the actuality so far that the effect of optimization searching in orthogonal design has not displayed completely because it is limited to be used in initializing the swarm or to be used in optimization searching only once in general application of evolution calculation. We not only break the limitation of only once searching in the orthogonal optimization but also find out the method of confirmation for further searching direction and searching scale of orthogonal optimization which is based on the variance analysis and variance ratio analysis of orthogonal design. Moreover, using the characteristic of orthogonal design which is easy to find the optimal variable composition of the current optimal value and to find the variable interval which includes the optimal solution in one arrayed test or calculation, we put forward an orthogonal optimization algorithm of swarm intelligence optimization based on the analysis of variance ratio, which is able to be circulating in the optimization searching. Based on the further searching direction and searching scale supplied by the variance ratio analysis, the global optimal solution will be approached only by two generations of orthogonal evolution for orthogonal initialized swarm selected randomly and the accurate solution will be obtained within ten generations of orthogonal evolution if the orthogonal intelligent evolution is kept on doing. Through the simulation analysis for the Shubert multi-peaked function, it shows the orthogonal optimization algorithm of swarm intelligence optimization based on the analysis of variance ratio is much better than other current algorithms of intelligent optimization because the former has less calculation amount, shorter searching time, more rapid speed and higher accuracy of optimization searching than the latter and is without deficiency of premature or slow convergence. This new algorithm is not only suitable to solve both the unimodal function and the multi-modal function problems but also is worthy of generalizing into the practical application since the orthogonal array is very easy to be used and popularized.
Starting Page	389
Ending Page	392
File Size	334545
Page Count	4
File Format	PDF
ISBN	9780769538655
DOI	10.1109/ISCID.2009.106
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Ant colony optimization Educational institutions Competitive intelligence Particle swarm optimization Analysis of variance Computational intelligence Design optimization Genetic algorithms Convergence
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Swarm Intelligence Optimization Algorithm Based on Orthogonal Optimization

The Variations, Combination Strategies Analysis of Particle Swarm Optimization

A New Improved Particle Swarm Optimization Algorithm

The Overview of Feature Selection Algorithms Based Swarm Intelligence and Rough Set

Comparative Study on Bionic Optimization Algorithms for Sewer Optimal Design

Thermal Unit Commitment using improved ant colony optimization algorithm via Lagrange multipliers

An Artificial Bee Colony Optimization Algorithm Based on Multi-exchange Neighborhood

Data clustering algorithms based on Swarm Intelligence

On the Analysis of Performance of the Artificial Searching Swarm Algorithm

Orthogonal Optimization Algorithm of Swarm Intelligence Based on the Analysis of Variance Ratio

Similar Documents

Swarm Intelligence Optimization Algorithm Based on Orthogonal Optimization

The Variations, Combination Strategies Analysis of Particle Swarm Optimization

A New Improved Particle Swarm Optimization Algorithm

The Overview of Feature Selection Algorithms Based Swarm Intelligence and Rough Set

Comparative Study on Bionic Optimization Algorithms for Sewer Optimal Design

Thermal Unit Commitment using improved ant colony optimization algorithm via Lagrange multipliers

An Artificial Bee Colony Optimization Algorithm Based on Multi-exchange Neighborhood

Data clustering algorithms based on Swarm Intelligence

On the Analysis of Performance of the Artificial Searching Swarm Algorithm

Orthogonal Optimization Algorithm of Swarm Intelligence Based on the Analysis of Variance Ratio