A novel genetic algorithm based on immunity
Top Cited Papers
- 1 September 2000
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans
- Vol. 30 (5), 552-561
- https://doi.org/10.1109/3468.867862
Abstract
A novel algorithm, the immune genetic algorithm (IGA), is proposed based on the theory of immunity in biology which mainly constructs an immune operator accomplished by two steps: 1) a vaccination and 2) an immune selection. IGA proves theoretically convergent with probability 1. Strategies and methods of selecting vaccines and constructing an immune operator are also given. IGA is illustrated to be able to restrain the degenerate phenomenon effectively during the evolutionary process with examples of TSP, and can improve the searching ability and adaptability, greatly increase the convergence rate.Keywords
This publication has 8 references indexed in Scilit:
- Combinatorial optimization with use of guided evolutionary simulated annealingIEEE Transactions on Neural Networks, 1995
- Convergence analysis of canonical genetic algorithmsIEEE Transactions on Neural Networks, 1994
- APPLYING EVOLUTIONARY PROGRAMMING TO SELECTED TRAVELING SALESMAN PROBLEMSCybernetics and Systems, 1993
- Control system optimization using genetic algorithmsJournal of Guidance, Control, and Dynamics, 1992
- PARALLEL GENETIC ALGORITHMS IN COMBINATORIAL OPTIMIZATIONPublished by Elsevier BV ,1992
- System identification and control using genetic algorithmsIEEE Transactions on Systems, Man, and Cybernetics, 1992
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of ImagesIeee Transactions On Pattern Analysis and Machine Intelligence, 1984
- Cognitive systems based on adaptive algorithmsACM SIGART Bulletin, 1977