Communications of the ACM
The zero/one multiple knapsack problem and genetic algorithms
SAC '94 Proceedings of the 1994 ACM symposium on Applied computing
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
An Evolutionary Immune Network for Data Clustering
SBRN '00 Proceedings of the VI Brazilian Symposium on Neural Networks (SBRN'00)
The Architecture For A Hardware Immune System
EH '01 Proceedings of the The 3rd NASA/DoD Workshop on Evolvable Hardware
Self-Nonself Discrimination in a Computer
SP '94 Proceedings of the 1994 IEEE Symposium on Security and Privacy
Anomaly Detection Using Real-Valued Negative Selection
Genetic Programming and Evolvable Machines
Solving Multiobjective Optimization Problems Using an Artificial Immune System
Genetic Programming and Evolvable Machines
How Do We Evaluate Artificial Immune Systems?
Evolutionary Computation
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Intrusion detection using sequences of system calls
Journal of Computer Security
Predictive models for the breeder genetic algorithm i. continuous parameter optimization
Evolutionary Computation
A dynamic artificial immune algorithm applied to challenging benchmarking problems
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Immune inspired somatic contiguous hypermutation for function optimisation
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Combining mutation operators in evolutionary programming
IEEE Transactions on Evolutionary Computation
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
An orthogonal genetic algorithm with quantization for globalnumerical optimization
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Learning and optimization using the clonal selection principle
IEEE Transactions on Evolutionary Computation
Hybrid Taguchi-genetic algorithm for global numerical optimization
IEEE Transactions on Evolutionary Computation
A novel genetic algorithm based on immunity
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
The abstract immune system algorithm
UC'07 Proceedings of the 6th international conference on Unconventional Computation
Hi-index | 0.00 |
Inspired by the clonal selection theory together with the immune network model, we present a new artificial immune algorithm named the immune memory clonal algorithm (IMCA). The clonal operator, inspired by the immune system, is discussed first. The IMCA includes two versions based on different immune memory mechanisms; they are the adaptive immune memory clonal algorithm (AIMCA) and the immune memory clonal strategy (IMCS). In the AIMCA, the mutation rate and memory unit size of each antibody is adjusted dynamically. The IMCS realizes the evolution of both the antibody population and the memory unit at the same time. By using the clonal selection operator, global searching is effectively combined with local searching. According to the antibody-antibody (Ab-Ab) affinity and the antibody-antigen (Ab-Ag) affinity, The IMCA can adaptively allocate the scale of the memory units and the antibody population. In the experiments, 18 multimodal functions ranging in dimensionality from two, to one thousand and combinatorial optimization problems such as the traveling salesman and knapsack problems (KPs) are used to validate the performance of the IMCA. The computational cost per iteration is presented. Experimental results show that the IMCA has a high convergence speed and a strong ability in enhancing the diversity of the population and avoiding premature convergence to some degree. Theoretical roof is provided that the IMCA is convergent with probability 1.