NDLI: Enhanced differential evolution using random-based sampling and neighborhood mutation

Content Provider	Springer Nature Link
Author	Liu, Gang Xiong, Caiquan Guo, Zhaolu
Copyright Year	2014
Abstract	Differential evolution (DE) is a simple and efficient global optimization algorithm. When differential evolution is applied in complex optimization problems, it has the shortages of prematurity and stagnation. An enhanced differential evolution using random sampling and neighborhood mutation to solve the above problems is proposed in this paper. The proposed enhanced DE is called random-based differential evolution with neighborhood mutation (NRDE). Random-based sampling is an improvement of center-based sampling. In NRDE, random-based sampling as the new mutation operator to generate the random-based individuals and the designed neighborhood mutation operator are used to search in the neighborhood created by the centers of the population and the sub-population. This paper compares other state-of-the-art evolutionary algorithms with the proposed algorithm, NRDE. Experimental verifications are conducted on 24 benchmark functions and the CEC’05 competition, including detailed analysis for NRDE. The results clearly show that NRDE outperforms other evolutionary algorithms in terms of the solution accuracy and the convergence rate.
Starting Page	2173
Ending Page	2192
Page Count	20
File Format	PDF
ISSN	14327643
Journal	Soft Computing
Volume Number	19
Issue Number	8
e-ISSN	14337479
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2014-07-29
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Differential evolution Random-based sampling Neighborhood mutation Global optimization Computational Intelligence Artificial Intelligence (incl. Robotics) Mathematical Logic and Foundations Control, Robotics, Mechatronics
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Software Geometry and Topology

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

Improving the performance of differential evolution algorithm using Cauchy mutation

Cellular direction information based differential evolution for numerical optimization: an empirical study

Enhanced opposition-based differential evolution for solving high-dimensional continuous optimization problems

Learning-enhanced differential evolution for numerical optimization

DE/BBO: a hybrid differential evolution with biogeography-based optimization for global numerical optimization

An improved memetic algorithm using ring neighborhood topology for constrained optimization

Localized biogeography-based optimization

Three modified versions of differential evolution algorithm for continuous optimization

Heterozygous differential evolution with Taguchi local search

Enhanced differential evolution using random-based sampling and neighborhood mutation

Similar Documents

Improving the performance of differential evolution algorithm using Cauchy mutation

Cellular direction information based differential evolution for numerical optimization: an empirical study

Enhanced opposition-based differential evolution for solving high-dimensional continuous optimization problems

Learning-enhanced differential evolution for numerical optimization

DE/BBO: a hybrid differential evolution with biogeography-based optimization for global numerical optimization

An improved memetic algorithm using ring neighborhood topology for constrained optimization

Localized biogeography-based optimization

Three modified versions of differential evolution algorithm for continuous optimization

Heterozygous differential evolution with Taguchi local search

Enhanced differential evolution using random-based sampling and neighborhood mutation