NDLI: A Cluster and Gradient-Based Artificial Immune System Applied in Optimization Scenarios

Content Provider	IEEE Xplore Digital Library
Author	de Mello Honorio, L. da Silva, A.M.L. Barbosa, D.A.
Copyright Year	1997
Abstract	The main objective of this paper is to use artificial immune systems (AIS) in optimization problems. For this purpose, two major immunological principles presented in the literature are revisited: hypermutation, which is responsible for local search, and receptor edition, used to explore different areas in the solution space. This paper presents three major modifications divided into two different goals. The first goal is to speed up the convergence of each individual. This is done through a new hypermutation approach that uses the numerical information provided by the optimization system to drive the cloning process to interesting directions into the solution space. The second goal regards the reduction of the computational effort necessary to simulate the whole population. This is accomplished by adding to the AIS algorithm two more features of the natural immune system: maturation control and memory cells. The maturation control analyzes the antibodies and, during the convergence process, eliminates possible redundancies, represented by individuals driving to the same local optimum. The last proposed improvement is the use of memory cells in dynamic-optimization scenarios. In such situations, a repertoire of successful cases is used to forecast part of the initial population. Combining these concepts together decreases the number of antibodies, generations, and clones, consequently speeding up the convergence process. Applications illustrate the performance of the proposed method.
Starting Page	301
Ending Page	318
Page Count	18
File Size	23432958
File Format	PDF
ISSN	1089778X
Volume Number	16
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optimization Immune system Cloning Vectors Convergence Clustering algorithms TV nonlinear optimization Artificial immune systems clustering gradient-based algorithms
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Computational Theory and Mathematics Software

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

A Novel Immune Clonal Algorithm for MO Problems

A quasi-gradient and cluster-based artificial immune system for dynamic optimization

On FNM-based and RFCM-based fuzzy co-clustering algorithms

FaiNet: An immune algorithm for fuzzy clustering

The impact of cluster representatives on the convergence of the K-modes type clustering

Immune engineering for Elgasir algorithm optimization

Structure optimization of fuzzy neural network using rough set theory

A Convergence Theorem for the Fuzzy ISODATA Clustering Algorithms

An artificial immune cell model based C-means clustering algorithm

A Cluster and Gradient-Based Artificial Immune System Applied in Optimization Scenarios

Similar Documents

A Novel Immune Clonal Algorithm for MO Problems

A quasi-gradient and cluster-based artificial immune system for dynamic optimization

On FNM-based and RFCM-based fuzzy co-clustering algorithms

FaiNet: An immune algorithm for fuzzy clustering

The impact of cluster representatives on the convergence of the K-modes type clustering

Immune engineering for Elgasir algorithm optimization

Structure optimization of fuzzy neural network using rough set theory

A Convergence Theorem for the Fuzzy ISODATA Clustering Algorithms

An artificial immune cell model based C-means clustering algorithm

A Cluster and Gradient-Based Artificial Immune System Applied in Optimization Scenarios